Estimates of Newman Sum over Numbers Multiple of a Fixed Integer

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高二英语经济预测单选题50题

高二英语经济预测单选题50题

高二英语经济预测单选题50题1. The GDP of a country measures the total value of all final goods and services produced within a country's borders _.A. in a given yearB. for several yearsC. since its establishmentD. in a future year答案:A。

解析:GDP(国内生产总值)是衡量一个国家在特定的一年里,在其境内生产的所有最终商品和服务的总价值。

选项A“in a given year” 在给定的一年)符合GDP的定义中关于时间的界定。

选项B“for several years” 好几年)不是GDP计算的常规时间跨度。

选项C“since its establishment”(自从它建立以来)这种时间界定不符合GDP的计算方式。

选项D“in a future year”(在未来的一年),GDP 是对已经发生的生产成果的衡量,不是未来的。

2. Inflation refers to _.A. a decrease in the general price levelB. an increase in the general price levelC. a stable price levelD. a random change in price level答案:B。

解析:通货膨胀(Inflation)指的是总体物价水平的上升。

选项A“a decrease in the general price level” 总体物价水平下降)是通货紧缩的概念。

选项C“a stable price level”( 稳定的物价水平)与通货膨胀概念相悖。

选项D“a random change in price level”(物价水平随机变化)没有准确表达通货膨胀是物价上升这一概念。

高二英语经济趋势单选题50题

高二英语经济趋势单选题50题

高二英语经济趋势单选题50题1. The GDP of a country is often considered as an important indicator of its economic _____.A. strengthB. weaknessC. problemD. solution答案:A。

解析:GDP(国内生产总值)通常被视为一个国家经济实力(strength)的重要指标。

选项B“weakness”( 弱点)与GDP作为积极的经济衡量指标相悖;选项C“problem”( 问题)不能准确描述GDP与经济的关系,GDP是一种衡量方式而不是问题本身;选项D“solution” 解决方案)也不符合GDP的性质,它不是一种解决方案。

2. Inflation means that the general level of prices for goods and services is _____.A. risingB. fallingC. stableD. disappearing答案:A。

解析:通货膨胀(Inflation)的定义就是商品和服务的总体价格水平在上升(rising)。

选项B“falling”( 下降)是通货紧缩的情况;选项C“stable”( 稳定)与通货膨胀概念不符;选项D“disappearing”消失)完全不符合价格水平与通货膨胀的关系。

3. High unemployment rate may lead to a decrease in _____.A. consumer spendingB. production capacityC. both A and BD. none of the above答案:C。

解析:高失业率意味着很多人没有工作也就没有收入,这会导致消费支出(consumer spending)减少,同时企业因为需求减少也会降低生产能力 production capacity),所以选项C正确。

计量经济学中英文词汇对照

计量经济学中英文词汇对照
Cronbach α (alpha)
cross-loading Cross-over design Cross-section analysis Cross-section survey
Cross-sectional
Crosstabs Cross-tabulation table Cube root Cumulative distribution function Cumulative probability Curvature Curvature Curve fit Curve fitting Curvilinear regression Curvilinear relation Cut-and-try method Cycle
Controlled experiments Conventional depth Convolution Corrected factor Corrected mean Correction coefficient Correctness Correlation coefficient Correlation index Correspondence Counting Counts Covariance Covariant Cox Regression Criteria for fitting Criteria of least squares Critical ratio Critical region Critical value
Cyclist DDD D test Data acquisition Data bank Data capacity Data deficiencies Data handling Data manipulation Data processing Data reduction Data set Data sources Data transformation Data validity Data-in Data-out Dead time Degree of freedom Degree of precision Degree of reliability Degression Density function Density of data points Dependent variable Dependent variable Depth Derivative matrix Derivative-free methods Design Determinacy Determinant Determinant Deviation Deviation from average Diagnostic plot Dichotomous variable Differential equation Direct standardization Discrete variable DISCRIMINANT Discriminant analysis Discriminant coefficient

2023-2024学年山东省淄博市高一上学期期末考试英语试题

2023-2024学年山东省淄博市高一上学期期末考试英语试题

2023-2024学年山东省淄博市高一上学期期末考试英语试题Killer Our 100-Word-Story CompetitionOur much-loved 100-Word-Story Competition is back! Enter for the chance to win prizes of up to £1,000. It is your opportunity to show the world your storytelling talents!Rules and prizesPlease make sure that compositions are original, not published before. Just write exactly 100 words (not including title) —not a single word shorter or longer! Don’t forget to inclu de your full name, address, email and phone number when filling in the form. We may use entries (参赛作品) in all print and electronic media.There are three age groups — one for adults and two for schools: one for children aged 12-18 and one for children under 12. The winner of each group will receive £1,000 and the one in the second place will receive £250.Terms and conditionsEntries are now open and the cut-off date is February 1, 2024, either online or by post addressed to:Reader’s Digest100 Word Story CompetitionWarners Group PublicationsWest StreetBournePE10 9PHThe editorial team will pick a shortlist of entries, and the three best stories in each group will be posted online at on March 1. You can vote for your favorite, and the one with the most votes will win the top prize. Voting will close on March 31. The winner list will be posted online on April 16 and the winning entries will be published in our May 2024 issue.Enter your story here— good luck!1. Which of the following will result in disqualification?A.Never being published before. B.Mailing your entry on January 31.C.Writing a story of 120 words. D.Creating a story originally.2. Who determines the winning entries?A.Editors and voters. B.Children under12.C.The media. D.The publisher.3. When will the winning entries come out?A.In February. B.In March. C.In April. D.In May.The Chinese pancake, or jianbingguozi, is one of the most common breakfast foods in northern China, usually filled with materials like vegetables, eggs and spicy paste. On the video-sharing platform Douyin, French chef Corentin Delcroix’s video of his own type of jianbing has been viewed about 250,000 times. But just how does his differ? It is packed with cheese, ham, pickle (泡菜) and black truffle mayonnaise (黑松露蛋黄酱) — materials typically found in French pancakes, which Delcroix says aren’t all that different to Chinese pancakes.Delcroix’s addiction to Chinese cuisine started in 2002 when he was studying in Beijing. “The first Chinese dish I learned to cook was scrambled eggs with tomatoes. But my favorites are cooked wheat-based foods such as jiaozi and xiaolongbao,’” says Delcroix. After lea rning how to prepare some of the popular local dishes, Delcroix decided to share his favorite Chinese and French dishes on social media. And many of his videos show him preparing dishes that marry elements of both cuisines.But this effort is not just about self-improvement — Delcroix says he has also managed to learn more about Chinese cuisines through the comments that he receives from his viewers. “It is through the viewers that I get to learn how to create truly local dishes. The suggestions are faster and more direct than those from the market,” Delcroix says.Delcroix is presently a chef, a successful businessman and a food blogger who has millions of followers on Chinese social media platforms. Despite having learned so much about Chinese cuisine over the years, Delcroix is still hungry for more knowledge.Looking ahead, he wants to do more to spread Chinese cuisine to people overseas. “I always feel that there might be cultural barriers when Chinese chefs introduce their local cuisines to foreigners. It might be much easier for a foreigner to explain,” he adds, “I want to be that bridge.”4. Which is the feature of Delcroix’s video?A.It introduces Chinese cuisine. B.It mainly shows wheat-based foods.C.It combines two countries’ cuisines.D.It shares how to make special jianbing .5. What does the underlined word “those” in paragraph 3 refer to?A.The ChineseB.The suggestions. C.The local dishes. D.The viewers.cuisines.6. Why does Delcroix want to be a bridge?A.To open a Chinese restaurant in France.B.To get more knowledge of Chinese cuisine.C.To introduce more delicious food to his fans.D.To improve foreigners’ understanding of Chinese cuisine.7. Which of the following best describes Delcroix?A.Creative and determined. B.Professional but negative.C.Humorous and talented. D.Curious but impatient.It’s clear that following a plant-based diet is connected with a lower risk of heart disease. There are many types of plant-based diets, and they are all related to certain foods connected with heart benefits, such as whole grains, fruits, vegetables, nuts and healthy oils. The diets have been most studied for their impact on heart health. These diets are rich in vitamins and minerals that help lower blood pressure, reduce the risk of diabetes (糖尿病) and keep a healthy weight, all of which can lower your risk of heart disease.Yet, the types of plant foods and their sources are also important. For example, white rice and white bread are plant-based foods, so you would think the y’re good to eat. But they are highly processed, and so are depleted of many heart-healthy nutrients (营养) and have enough sugar, which means they can make blood sugar levels rise sharply and increase hunger, leading to overeating. Drinking 100% fruit juice is not the same as eating the whole fruit, since juices can be high in sugar.Do you really have to cut out all meat for your heart’s health? Which animal foods could have an impact on heart health? Some research has shown that the type and amount matter most. A 2014 study showed that men aged 45 to 79 who ate 75 grams or more per day of processed red meat, like cold cuts, sausage, bacon and hot dogs, had a 28% higher risk of heart failure than those who ate less than 25 grams. However, a study in the January 2017 found that eating 85 grams of unprocessed red meat, three times per week, did not worsen blood pressure.What is the right plant-based diet for you? “For many men, this may be a matter of bettering their current foods,” says Dr. Satija, a research er from American College of Cardiology.8. From the first two paragraphs, we know that plant-based diets ________.A.benefit heart health B.increase hunger C.lead tooverweightD.contain enoughsugar9. What do the underlined words “depleted of’’ in parag raph 2 mean?A.Added to. B.Short of. C.Filled with. D.Rooted in.10. Why does the author list numbers in paragraph 3?A.To prove the result believable. B.To attract readers’ attention.C.To show the process clearly. D.To make the study popular.11. What might the author continue talking about?A.Risks of animal foods. B.Disadvantages of plant-based diets.C.Changes of eating habits. D.Effects of heart-healthy diets.The dry land in Gir National Park and Wildlife Preserve, located near India western tip, is the proud — and only — home of the Asiatic lion. By the early 1900s, however, their populations haddecreased for homo loss and hunting, leaving fewer than 50 known individuals alive. Though their numbers have risen over the past several decades — climbing to around 670 in 2020, a successful story — the lions are still considered endangered.One of the biggest challenges to keep the lions’ future is to track them, a hard work. Some animals, like tigers and zebras, have special coat patterns (图案) that provide useful marks to the researchers. But for the Asiatic lions, researchers must look elsewhere.In 2019, Banerjee, who worked for Indias National Tiger Conservation Authority, developed an AI system to recognize the lions with high accuracy (精准). The AI program, SIMBA, has been applied in practice. “It will be a fantastic tool for long-term lion monitoring,” says Banerjee. He adds, “It could help forest officials arrive at a more accurate estimate (评估) of Gir’s lion population. In a few years, the group will have a rich collection of information — how many lions are male, female, how many will bear babies and how many are dead.”Despite the advantages, Baneijee also adds his worries. He suggests certain rules be made to prevent main information from bei ng stolen. “Where tools like SIMBA really shine”, he says, “is in helping researchers develop monitoring plans that are keys to the protection of at-risk animals,” he says, “otherwise, all your efforts will be in vain.”12. What is the greatest difficulty in protecting Asiatic lions?A.Stopping them from being killed. B.Keeping track of them.C.Protecting their living environment. D.Increasing their population.13. How does SIMBA help researchers?A.By locating lions’ homes.B.By tracking other animals.C.By monitoring the animal stealers. D.By providing accurate information.14. What’s Baneijee’s opinion about the AI program?A.It needs to be widely used. B.It has saved the at-risk animals.C.Its possible risks should be aware of. D.Its disadvantages should be ignored.15. Which can be a suitable title for the text?A.The Application of AI on Protecting Animals. B.The AI Program for the Endangered Asiatic Lions.C.The Measures of Protecting AsiaticLions.D.The Biggest Challenge of the AI system.Higher levels of optimism (乐观主义) are related lo a longer lifetime. People with the highest levels of optimism have 11 % to 15% longer lifetime than those who practice little positive thinking. The optimists may live to age 85 or beyond.Optimism doesn’t mean ignoring life’s stress. But when negative things happen, optimistic people are less likely to blame themselves. 16 . They also believe they can control their destiny and create opportunities for good things to happen in the future.17 . Research has f ound optimists have a 35% less chance of a heart disease. There’s a direct connection between optimists and healthier diet and exercise behaviors, as well as a stronger immune (免疫) system and better lung function.Optimism can be improved by training. Studies have found only about 25% of our optimism is programmed by genes (基因). 18 . It turns out you can train your brain to be more positive. One of the most effective ways to increase optimism is called the “Best Possible Self” method. In this period, you imagine yourself in future, and you have achieved all your life aims and all of your problems have been solved. 19 . Another way is to keep a journal only to capture positive experiences you experienced that day.It’s not easy to carry out optimism exercis es. Like exercise, they will need to be practiced regularly to keep the brain positive. 20 . But isn’t a longer, happier, more positive life worth the effort?Esbon Kamau had a normal Tuesday afternoon picking up passengers in Hoover.On this particular day, he had the pleasure of driving Alex Tisdale, a 16-year-old who eagerly_______ the exciting news of receiving an $8,000 Christmas gift from his proud father to _______ a new motorcycle.During the 15-minute _______ to John Hawkins Parkway, Tisdale left Kamau with a heart-warming impression. However, the _______ took place when Kamau noticed a blue bag at the back of his seat after _______ Tisdale to pick up another passenger.Upon examining the bag, Kamau _______ a large amount of money. Rather than keeping it, he decided to hold onto the money until he could report the _______ to the company. Meanwhile, Tisdale, unaware of the missing money then and there, _______ went back, wondering where he could have _______ it.Unable to find each other, they both used the company’s app to report the ________ article. Thanks to the company’s communication, they were ________ over the phone. Without hesitation, Kamau made the admirable ________ to drive back to Tisdale.Tisdale, ________ by Kamau’s honesty, expressed his thanks by tipping him $10. This act of kindness left a lasting ________ on Tisdale, who advised others to be grateful for what they have. At the same time, Kamau shared a piece of advice for fellow taxi drivers, ________ the importance of doing the right thing at the right time.21.A.shared B.collected C.ignored D.kept22.A.ride B.buy C.borrow D.choose23.A.goal B.adventure C.chance D.journey24.A.unexpected B.forgotten C.respected D.unavoidable25.A.putting down B.learning about C.dropping off D.sending out26.A.emptied B.required C.discovered D.guessed27.A.opinion B.information C.preparation D.knowledge28.A.calmly B.angrily C.excitedly D.anxiously29.A.watched B.returned C.left D.searched30.A.missing B.wild C.strange D.disappearing 31.A.introduced B.compared C.recognized D.connected32.A.result B.decision C.solution D.purpose33.A.surprised B.saved C.satisfied D.moved34.A.impression B.debate C.attention D.comment35.A.exploring B.exchanging C.stressing D.reflecting36. Words ________ (form) by combining other words are called compounds. (所给词的适当形式填空)37. Should the brothers have been disqualified or highly praised ________ their actions? (用适当的词填空)38. With a different theme each year, the day ________ (observe) with a wide range of events that are organized at local, national and international levels. (所给词的适当形式填空)39. When you ________ (strike) the match to light your cigar I saw it was the face of the man wanted in Chicago. (所给词的适当形式填空)40. Last spring in Yellowstone, I followed a path_____ took me through a dark forest. (用适当的词填空)41. I gathered all my courage to take ________ bite and was amazed to find it was not bad. (用适当的词填空)42. While I was concentrating on photographing this amazing scene, I suddenly had a feeling that I was ________ (watch). (所给词的适当形式填空)43. Starting in the Yuan Dynasty, work on the terraces took hundreds of years, until its ________ (complete) in the early Qing Dynasty. (所给词的适当形式填空)44. With his________ (limit) imagination, he created new literature worlds for his readers to explore.(所给词的适当形式填空)45. How would you feel if moving to a new town meant _____(lose) track of your friends. (所给单词适当形式填空)46. 假定你是李华,目前在英国参加一个交流项目,住在Mrs. Smith家。

商务英语中数字增长下降的表述

商务英语中数字增长下降的表述

•中国6月份工业产出同比涨幅出现骤降,从5月 份的16.5%降至13.7%,进一步加深了经济增长 显著减速的印象。 •The impression of a significant slowdown was reinforced by a sharp drop in the year-on-year growth of industrial production in June, falling to 13.7 per cent from 16.5 per cent in May.

1/24/2019
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《中华人民共和国2004年国民经济和社会发展统计公报》 第一产业增加值20744亿元,增长6.3%。 The added value of the primary industry was 2,074.4 billion yuan, up by 6.3 percent(up 6.3 percent).

1/24/2019
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《中国6月份汽车销量劲升48%》-《金融时报》-2009-07-10 昨日公布的数据显示,中国6月份乘用车销售较去年同期增长了48%。 China's passenger car sales rose 48 per cent in June on the same month last year, according to data released yesterday. 今年上半年,中国汽车总销售量同比增长18% total vehicles sales rose 18 per cent for the first half year to 6.1m from the same period last year
7月出口同比增长38.1%,增速其实已经较6月的 43.9%有所放缓。但进口增长放缓更多,从6月的 34.1%减速到22.7% The pace of increase in exports actually fell last month to 38.1 per cent, year-on-year, down from 43.9 per cent in June. However, import growth slowed even more, moving up 22.7 per cent against 34.1 per cent长48%,同比激增 74.4%。

计量选择

计量选择

Quiz ——Multiple ChoiceName Student Number Scores1. An estimator is(A) an estimate.(B) a formula that gives an efficient guess of the true population value.(C) a random variable.(D) a nonrandom number.2. An estimate is(A) efficient if it has the smallest variance possible.(B) a nonrandom number.(C) unbiased if its expected value equals the population value.(D) another word for estimator.3. An estimator ˆY μof the population value Y μ is unbiased if (A) ˆY Y μμ=. (B) Y has the smallest variance of all estimators. (C) pY Y μ→. (D) ˆ()Y Y E μμ=. 4. The standard error of ˆ, ()Y Y SE Y σ= is given by the following formula: (A) 211()n i i Y Y n =-∑. (B) 2Y s n . (C) Y s .(D) . 5. A type I error is(A) always the same as (1-type II) error.(B) the error you make when rejecting the null hypothesis when it is true.(C) the error you make when rejecting the alternative hypothesis when it is true.(D) always 5%.6. A type II error(A) is typically smaller than the type I error.(B) is the error you make when choosing type II or type I.(C) is the error you make when not rejecting the null hypothesis when it is false.(D) cannot be calculated when the alternative hypothesis contains an “=”.7. When you are testing a hypothesis against a two-sided alternative, then the alternative is written as(A) ,0()Y E Y μ>. (B) ,0()Y E Y μ=. (C) ,0Y Y μ≠. (D) ,0()Y E Y μ≠.8. If the null hypothesis states 0,0:()Y H E Y μ=, then a two-sided alternative hypothesis is(A) 1,0:()Y H E Y μ≠. (B) 1,0:()Y H E Y μ≈.(C) 1,0:Y Y H μμ<. (D) 1,0:()Y H E Y μ>9. A scatterplot(A) shows how Y and X are related when their relationship is scattered all over theplace.(B) relates the covariance of X and Y to the correlation coefficient.(C) is a plot of n observations on i X and i Y , where each observation isrepresented by the point (,i i X Y ).(D) s hows n observations of Y over time.10. A large p -value implies(A) rejection of the null hypothesis.(B) a large t -statistic.(C) a large act Y .(D) that the observed value act Y is consistent with the null hypothesis.11. The standard error for the difference in means if two random variables M and W ,when the two population variances are different, is(A) (B) W M M W s s n n +.(C)(D) . 12. The following statement about the sample correlation coefficient is true.(A) –1XY r ≤≤1. (B) 2(,)pXY i i r corr X Y →.(C) ||1XY r <. (D) 222XY XY X Y s r s s =. 13. The correlation coefficient(A) lies between zero and one.(B) is a measure of linear association.(C) is close to one if X causes Y .(D) takes on a high value if you have a strong nonlinear relationship.14.When the estimated slope coefficient in the simple regression model, 1ˆβ, is zero, then(A) R 2 = Y . (B) 0 < R 2 < 1. (C) R 2 = 0. (D) R 2 > (SSR /TSS ).15. The regression 2R is defined as follows:(A) ESS TSS (B) RSS TSS(C) ()()n i i Y Y X X --∑ (D) 2SSR n - 16. The standard error of the regression (SER ) is defined as follows(A) 2112n i i u n =-∑ (B) SSR (C) 1-2R (D) 2111n i i u n =-∑ 17. Binary variables(A) are generally used to control for outliers in your sample.(B) can take on more than two values.(C) exclude certain individuals from your sample.(D) can take on only two values.18. The following are all least squares assumptions with the exception of:(A) The conditional distribution of i u given i X has a mean of zero.(B) The explanatory variable in regression model is normally distributed.(C) (,),1,...,i i X Y i n = are independently and identically distributed.(D) Large outliers are unlikely.19. The OLS estimator is derived by(A) connecting the Y i corresponding to the lowest X i observation with the Y icorresponding to the highest X i observation.(B) making sure that the standard error of the regression equals the standard errorof the slope estimator.(C) minimizing the sum of absolute residuals.(D) minimizing the sum of squared residuals.20. The OLS estimator is derived by(A) connecting the Y i corresponding to the lowest X i observation with the Y icorresponding to the highest X i observation.(B) making sure that the standard error of the regression equals the standard errorof the slope estimator.(C) minimizing the sum of absolute residuals.(D) minimizing the sum of squared residuals.21. The OLS residuals, i u , are defined as follows:(A) 01i i Y X ββ-- (B) 01i i Y X ββ-- (C) i i Y Y - (D) 2()i Y Y -22. The OLS residuals(A) can be calculated using the errors from the regression function.(B) can be calculated by subtracting the fitted values from the actual values.(C) are unknown since we do not know the population regression function.(D) should not be used in practice since they indicate that your regression does notrun through all your observations.23. The slope estimator, β1, has a smaller standard error, other things equal, if(A) there is more variation in the explanatory variable, X .(B) there is a large variance of the error term, u .(C) the sample size is smaller.(D) the intercept, β0, is small.24. In the linear regression model, i i i u X Y ++=10ββ, i X 10ββ+ is referred to as(A) the population regression function. (B) the sample regression function.(C) exogenous variation. (D) the right-hand variable or regressor.25. E(u i | X i ) = 0 says that(A) dividing the error by the explanatory variable results in a zero (on average).(B) the sample regression function residuals are unrelated to the explanatoryvariable.(C) the sample mean of the Xs is much larger than the sample mean of the errors.(D) the conditional distribution of the error given the explanatory variable has azero mean.26. Multiplying the dependent variable by 100 and the explanatory variable by100,000 leaves the(A) OLS estimate of the slope the same.(B) OLS estimate of the intercept the same.(C) regression R 2 the same.(D) variance of the OLS estimators the same.27. Heteroskedasticity means that(A) homogeneity cannot be assumed automatically for the model.(B) the variance of the error term is not constant.(C) the observed units have different preferences.(D) agents are not all rational.28. The t -statistic is calculated by dividing(A) the OLS estimator by its standard error.(B) the slope by the standard deviation of the explanatory variable.(C) the estimator minus its hypothesized value by the standard error of theestimator.(D) the slope by 1.96.29. The confidence interval for the sample regression function slope(A) can be used to conduct a test about a hypothesized population regressionfunction slope.(B) can be used to compare the value of the slope relative to that of the intercept.(C) adds and subtracts 1.96 from the slope.(D) allows you to make statements about the economic importance of yourestimate.30. In general, the t -statistic has the following form:(A)estimate-hypothesize value standard error of estimate . (B) estimator standard error of estimator . (C) estimator-hypothesize value standard error of estimator.(D) estimator-hypothesize value standard error of estimator . 31. Finding a small value of the p -value (e.g. less than 5%)(A) indicates evidence in favor of the null hypothesis.(B) implies that the t -statistic is less than 1.96.(C) indicates evidence in against the null hypothesis.(D) will only happen roughly one in twenty samples.32. A binary variable is often called a(A) dummy variable (B) dependent variable (C) residual (D) p ower of a test33. The error term is homoskedastic if(A) var(|)i i u X x = is constant for i = 1,…, n. (B) i X is normally distributed.(C) var(|)i i u X x = depends on x . (D) there are no outliers.34. Under imperfect multicollinearity(A) the OLS estimator cannot be computed.(B) two or more of the regressors are highly correlated.(C) the OLS estimator is biased even in samples of n > 100.(D) the error terms are highly, but not perfectly, correlated.35. In the multiple regression model, the adjusted R 2, 2R(A) cannot be negative.(B) will never be greater than the regression R 2.(C) equals the square of the correlation coefficient r .(D) cannot decrease when an additional explanatory variable is added.36. You have to worry about perfect multicollinearity in the multiple regressionmodel because(A) many economic variables are perfectly correlated.(B) the OLS estimator is no longer BLUE.(C) the OLS estimator cannot be computed in this situation.(D) in real life, economic variables change together all the time.37. Under imperfect multicollinearity(A) the OLS estimator cannot be computed.(B) two or more of the regressors are highly correlated.(C) the OLS estimator is biased even in samples of n > 100.(D) the error terms are highly, but not perfectly, correlated.38. In multiple regression, the 2R increases whenever a regressor is(A) added unless the coefficient on the added regressor is exactly zero.(B) added.(C) added unless there is heterosckedasticity.(D) greater than 1.96 in absolute value.39. You have to worry about perfect multicollinearity in the multiple regressionmodel because(A) many economic variables are perfectly correlated.(B) the OLS estimator is no longer BLUE.(C) the OLS estimator cannot be computed in this situation.(D) in real life, economic variables change together all the time.40.In the multiple regression model, the least squares estimator is derived by(A)minimizing the sum of squared prediction mistakes.(B)setting the sum of squared errors equal to zero.(C)minimizing the absolute difference of the residuals.(D)forcing the smallest distance between the actual and fitted values.。

The_consumption_upgrading_effect_of_the_citizenshi

The_consumption_upgrading_effect_of_the_citizenshi

Development Economics of China2023, VOL. 7, NO. 1, 38-42DOI: 10.47297/wspdecWSP2515-797306.20230701The consumption upgrading effect of the citizenship of migrant workers: An empirical studyYihan ZhuNanchang Hangkong University, Nanchan, Jiangxi, 330063, P. R. ChinaABSTRACTThe citizenship of migrant workers is conducive to expanding domesticdemand and promoting consumption, and many scholars haveconducted studies on the consumption effects brought about by thecitizenship of migrant workers. This paper explores the consumptionupgrading effect of the citizenship of migrant workers from theperspective of micro data by using the regression model of least squaresmethod using data from the China Household Finance Survey. The studyfinds that as the income and education level, social security level,willingness to settle in the city and life satisfaction of migrant workersincrease, they become more integrated into the city and their economicstatus, social security and self-identity improve, ultimately increasing theirconsumption level and optimising their consumption structure, achievingthe effect of consumption upgrading.KEYWORDSCitizenization of migrant workers; Consumption upgrading effect;Empirical analysis1 IntroductionSince the reform and opening up, a large number of migrant workers have continued to flock to urban areas to work in search of better living and working conditions, resulting in the transfer of labour from the agricultural sector to the non-agricultural sector. This process has provided hundreds of millions of cheap labour for China's economic development, improved the efficiency of resource allocation, promoted the development of urbanisation and economic development in China, and created huge social wealth. According to the 2016 and 2022 China Statistical Yearbook prepared by the National Bureau of Statistics, the proportion of China's year-end urban population has increased year-on-year from 45.86% in 2007 to 64.72% in 2021, which shows that China's urban population has increased year-on-year in recent years and urbanisation has developed significantly. In recent years, the group of migrant workers in China has been growing and more and more scholars are paying attention to the issue of migrant workers' urbanisation. The citizenship of migrant workers not only plays an important role in expanding urban and rural domestic demand, but also stimulates consumption growth, increases employment, promotes industrial structure optimisation and upgrading, increases urban housing expenditure, and has a positive effect on economic growth.According to the existing studies, the citizenship of migrant workers can effectively release the consumption potential of migrant workers and promote the economy. However, at present, the* Corresponding Author:Development Economics of Chinaconsumption level of migrant workers is still at a low level.[1][2]Studies on the consumption constraints of migrant workers' citizenship mainly include the social status of migrant workers, the amphibious consumption pattern separated from the family, and the coverage rate of basic pension insurance.[3][4] Previous scholars have put forward some policy recommendations on how to promote the consumption capacity of migrant workers and optimize the consumption structure.[5][6] However, few literatures have further studied the role of citizenization of migrant workers in promoting the consumption upgrading of migrant workers. Therefore, it is necessary to further study the consumption upgrading effect of citizenization of migrant workers on the basis of existing literatures2 Study design2.1 Model settingIn exploring the role of the citizenship of migrant workers on consumption upgrading, the following regression model was constructed here with reference to previous scholarly research and the specific variables selected. The method used in the regression model is the least squares (OLS) method:Con1i =β+β1citii+∑control+εi(1)Con2i =β+β1citii+∑control+εi(2)In equation (1)Con1iis the first explanatory variable representing the level of consumption ofmigrant workers, and in equation (2)Con2iis the second explanatory variable representing theconsumption structure of migrant workers.β0is the constant term,β1is the regression coefficient,and citiidenotes the core explanatory variable representing the level of citizenship of migrantworkers, and∑control denotes the set of control variables, andεidenotes the random disturbance term representing other factors outside the model that can influence the consumption upgrading of migrant workers.2.2 Description of variables2.2.1 Explanatory variable: Consumption upgradeIn this paper, we refer to Li Weijun et al.'s (2023) measure of consumption upgrading, and take the increase in consumption level and the optimisation of consumption structure as the measure of consumption upgrading.[7] Accordingly, the first explanatory variable consumption level (con1) is set to be expressed using the total consumption expenditure of migrant workers. As this absolute value indicator is large, it is treated logarithmically.In terms of optimising the consumption structure of the second explanatory variable, the consumption expenditure of migrant workers can be divided into subsistence consumption and developmental enjoyment consumption based on the type of consumption. Survival consumption includes clothing, food, local transport and housing costs. Developmental consumption includes education, communication, transport, health care, recreational and cultural services and services. The second explanatory variable, consumption structure (con2), is therefore expressed as the share of developmental enjoyment consumption in total consumption.2.2.2 Core explanatory variable: Migrant workers' citizenshipBased on the seven indicators of migrant workers' education level, income level, housing type, commercial insurance, unemployment protection, willingness to settle and satisfaction with life, a39Yihan Zhu 40principal component analysis was used to construct a citizenship index (citi) for migrant workers, which was used as the core explanatory variable. The seven indicators take into account the personal quality, economic status, insurance protection and self-perception of migrant workers, and can better represent the degree of citizenship of migrant workers.As this paper constructs indicators of the degree of citizenship of migrant workers based on seven indicators: education level, income level, housing type, commercial insurance, unemployment protection, willingness to settle, and satisfaction with life, using principal component analysis. Therefore, it is necessary to conduct a descriptive analysis of these seven indicators. These seven indicators can be directly obtained from the CHFS questionnaire. The seven indicators correspond to the questions in the CHFS questionnaire: A2012 (highest level of education completed), A2023lc (annual income), A2017b (type of housing currently lived in), F6001a (type of commercial insurance purchased), F3001 (whether there is unemployment insurance), A2022ha (whether they are willing to obtain an urban hukou in their location) and H3514 ( Feeling happy).2.2.3 Control variablesSince the factors affecting the consumption upgrading of migrant workers are diverse, a set of control variables is selected here to enhance the accuracy of the findings, referring to the practices of previous scholars such as Zhanbo Chen et al. (2021) and Chenghao Sun et al. (2020) : gender (gender), age (age), marital status (married), health (health), whether or not a member of a party (party), and Total assets (asset).[8][9] The explanations for each variable are shown in Table 6: the sample of individuals under 18 years of age is likely to have income from the household i.e. not financially independent and the level of consumption expenditure is not representative, so this category was excluded from the paper.2.3 Data sourcesThe data used in this paper are from the China Household Finance Survey 2019 (CHFS-2019). In order to screen out the migrant worker sample from it, residents with agricultural household registration and working in non-agricultural jobs in urban areas were defined as migrant workers by referring to Wang Xiaoqing (2022).[10] Therefore, after excluding the ineligible samples, a sample of 17,079 migrant workers was retained.3 Empirical analysis3.1 Regression analysisTable 1 shows the estimation results of the model. Model (1) is the effect of migrant workers' citizenship on consumption level, while model (2) is the effect of migrant workers' citizenship on consumption structure. Firstly, according to the results of model (1), the regression coefficient of the degree of citizenship of migrant workers (citi) is 0.264, with a p-value of less than 0.01, thus passing the significance test at the 1% level, which means that the increase in the degree of citizenship of migrant workers will drive up their consumption level.According to the regression results of model (2), the regression coefficient of the degree of citizenship of migrant workers (citi) is 0.0362, with a p-value less than 0.01. Therefore, it passes the significance test at the 1% level, so the increase in the degree of citizenship of migrant workers will also increase the proportion of development-oriented consumption. Among the control variables in model (2), the regression coefficient of health is significantly negative, indicating that the better theDevelopment Economics of China health status is, the lower the proportion of development-oriented consumption will be, which is due to the fact that health care consumption expenditure decreases when the health status is better.In summary, as migrant workers become more integrated into the city, their economic situation, social security and self-identity will improve, ultimately raising consumption levels and optimising the consumption structure, achieving the effect of consumption upgrading.3.2 Robustness testsThis section uses a replacement of the econometric model for robustness testing, by replacing the least squares method used in the previous section (OLS) regression model was changed to generalised least squares (GLS) regression. The regression coefficient of the degree of citizenship of migrant workers (citi) was determined to be significantly positive, and if the results were still significantly positive under different econometric models, the findings of this paper were robust. The regression coefficient of the degree of citizenship of migrant workers (citi) on the level of consumption (con1) is 0.112, which passes the significance test at the 1% level, indicating that the conclusion that the citizenship of migrant workers promotes the increase of consumption level is more robust. Similarly, the regression coefficient of 0.0369 for the degree of citizenship of migrant workers (citi) on consumption structure (con2) still passed the significance test at the 1% level, indicating that the conclusion that the citizenship of migrant workers enhances consumption structure is also relatively robust.In summary, this section can still conclude that the deepening of the citizenship of migrant workers increases consumption levels and optimises the consumption structure, ultimately leading to consumption upgrading, by replacing the econometric model. Therefore, the conclusions of this paper are robust and reliable.Tables 2. Table of robustness testTable 1. Estimates of the Consumption Escalation Effect of the Citizenship of Migrant WorkersVariablesCitiGenderAgeHealthMarriedPartyAssetConstant termSample sizeR-side Models (1)con10.263***(0.0379)-0.0421***(0.0113)-0.00967***(0.000395)0.00724(0.00606)0.185***(0.0139)0.0289(0.0231)0.215***(0.00372)8.549***(0.0552)17,0790.246Models (2)con20.0361***(0.0103)-0.00695***(0.00307)-0.00124***(0.000107)-0.0223***(0.00165)0.00137(0.00378)0.00152(0.00628)0.0244***(0.00101)0.290***(0.0150)17,0790.050Note: Standard errors in brackets, ***, ** and * indicate significant at the 1%, 5% and 10% levels respectively 41Yihan Zhu About the authorYihan Zhu is undergraduate of Nanchang Hangkong University, and her research field is migrant worker economy.References[1] Li X., Zhang R. (2015). Research on the relationship between citizenization of new generation migrant workers and economic growth based on empirical analysis. Chinese Management Information Technology, 03:144-146.[2] Jiang C., Han C. (2015). Tax support effect of migrant workers' citizenization: Theoretical interpretation and practical countermeasures. Social Sciences of Ningxia, 03:65-70.[3] Li X., Luo L. (2021). Migration patterns and migrant workers' consumption. China Agricultural Economic Review, 13(4):781-798.[4] Su J. (2013). Consumption and its effect on the process of urbanization of rural migrant workers. Thesis of Shaanxi Normal University, 4: 1-205.[5] Chen B., Lu M., Zhong N. (2015). How urban segregation distorts Chinese migrants' consumption?. World Development, 70:133-146.[6] Deng Z. (2019). The Internet consumer finance for new generation of migrant workers the influence of consumer behavior research. Thesis of Southwestern University of Finance and Economics. 7: 1-69.[7] Li W., Zhou Y., Wu Y. (2023). Hidden income: Housing provident fund system and residents' consumption upgrading. Consumer Economics, 02:33-44.[8] Chen Z., Huang W., Hao X. (2021). Research on the impact of mobile payment on Chinese rural consumption. Macroeconomic Research, 05: 123-141.[9] Sun C., Xie T. (2020). Empirical test on the impact of Internet consumer finance on household consumption upgrading. Statistics and Decision, 17:134-137.[10] Wang X. (2022). The influence of the housing security system for migrant workers in our country residence mode. Thesis of Southwestern University of Finance and Economics, 2: 1-160.VariablesCitiGenderAgeHealthMarriedPartyAssetConstant termSample sizeR-side Models (1)con10.112***(-0.0308)-0.0211***(-0.00774)-0.00686***(-0.000314)-0.00162(-0.00162)0.143***(-0.0106)0.0421**(-0.0174)0.206***(-0.00372)8.616***(-0.054)17,0790.215Models (2)con20.0369***(-0.00836)-0.00508**(-0.0021)-0.000788***(-8.52E-05)-0.0153***(-0.0153***)000423(-0.00289)-0.0041(-0.00471)0.0276***(-0.00101)0.201***(-0.0146)17,0790.056Note: Standard errors in brackets, ***, ** and * indicate significant at the 1%, 5% and 10% levels respectively 42。

The value of higher education 高等教育的价值

The value of higher education 高等教育的价值

For society:
to realize that everyone can do whatever job is suited to his brain and ability to understand that all jobs are necessary to society to master all the necessary know-how to do one’s job well
Educational Attainment and Synthetic Estimates of Work-Life Earnings

"At most ages, more education equates with higher earnings, and the payoff is most notable at the highest educational levels," said Jennifer Cheeseman Day, coauthor of the report.

For society:

The different expectations between educated and uneducated parents toward their children’s higher education are too obvious, testifying that only when parents receive higher education then their children—the future of the country-- are more likely to finish college education as well.

自考英语二(00015)Unit6 TextA 练习

自考英语二(00015)Unit6 TextA 练习

原则上,理论上
Bridging the Gap(P218)
basic grow invest
ideally called
now that wasteful accumulated where direct
将单词分类: 动词:grow invest called accumulated direct 形容词:basic wasteful direct 副词:ideally 连词:now that where
Section A (P219)
1. To obtain objective findings, scientists ___d_r_e_w_t_h_e_____ _c_o_n_c_lu__si_o_n_s_o_n__t_h_e_b_a_s_is__o_f_e_x_p_e_r_im__e_n_t_s_ (根据实验得出 结论).(on the basis of) 2. She is such a self-disciplined person that _sh_e__h_a_s_n_e_v_e_r _b_e_e_n_i_n_d_u_l_g_e_d_i_n__a_lc_o_h_o_l_(她从不沾酒).(indulge in) 3. When he loses his temper, he _is__n_o_t_r_e_sp_o_n__si_b_l_e_f_o_r_h_i_s_ _b_e_h_a_v_i_o_r_s_(对自己的行为不负责任).(be responsible for) 4. The result of being employed proves that m__y__te_a_c_h_i_n_g _e_x_p_e_r_ie_n_c_e__st_a_n_d_s__m_e__in__g_o_o_d_s_t_e_a_d_(我的从教经验对我 利). (stand...in good stead) 5. Figures show that fifty percent of road accidents _h_a_v_e__re_s_u_l_te_d__in__h_e_a_d__in_j_u_r_i_es__(导致头部受伤).(result in)

大学英语四级(2013年12月考试改革适用)模拟试卷318(题后含答案及解析)

大学英语四级(2013年12月考试改革适用)模拟试卷318(题后含答案及解析)

大学英语四级(2013年12月考试改革适用)模拟试卷318(题后含答案及解析)题型有:1. Writing 2. Listening Comprehension 3. Reading Comprehension 4. TranslationPart I Writing1.For this part, you are allowed 30 minutes to write a composition on an English idiom “It’s never too old to learn”. Do you support it or disapprove of it? Write down your ideas with 120 -180 words.正确答案:It’ s Never Too Old to Learn We have heard a lot of times that it’ s never too old to learn. Sometimes we don’t take it seriously, and find many excuses not to learn something new. To be frank, we need to learn no matter how old we are. On the one hand, with the fast development of science and technology, we must admit that if we don’t learn new things we are likely to be eliminated by our society. For example, Wechat has a very close relationship with our daily life, not only among the circle of friends, but also with other people. Much work is done through Wechat. Imagine everybody except you knows how to use Wechat, you may feel uncomfortable. On the other hand, learning new things helps us be more intelligent. Human brain is like a machine, and if we use it more it will work better: on the contrary, if we use it less, it will work worse. All in all, it’s never too old to learn. No matter how old we are, learning new things helps us maintain an active state of mind: we will be less likely to feel loneliness because we are with the world.解析:“活到老学到老”这句话我们每个人都耳熟能详。

单变量变异数分析

单变量变异数分析

Post Hoc Tests 事后比较
事后比较结果,采两两配对组别比较。从 Scheffe 方法作事后比较可以 看出以适用度而言,国外品牌显着高于国内品牌,国外品牌与组装电脑 没有显着差异,国内品牌与组装电脑没有显着差异。
范例结果整理如下:
1.叙述性统计量
2.变异数分析统计表
*P<.05 事后比较: 事后比较结果,以适用度而言,国外品牌显着高于国内品牌,国 外品牌与组装电脑没有显着差异,国内品牌与组装电脑没有显着 差异。
2.相依样本,有二种情形 (1)重复量数:同一组受测者, 重复接受多次(k)的测试以比较 之间的差异 (2)配对组法:选择一个与依变数有关控制配对条件完全相同, 以比较k组受测者在依变数的差异
10-3 变异数分析的基本假设条件
变异数分析的基本假设条件有常态、线性、变异数同质 性。我们介绍如下:
常态:直方图, 偏度(skewness)和峰度(kcat osis), 检定, 改正 (非常态可以透过资料转型来改正)
计算t值 t值 = u1 (平均数) - u2 (平均数) / 组的平均数标准差 u1 是第一组的平均数 u2 是第二组的平均数
查t crit标准值 在研究者指定可接受t分配型态 I (type I) 错误机率a (例如: 0.05或0.01) 样本1和样本2的degree of freedm = (N1+N2) – 2 我们可以透过查表, 得到 t crit标准值
➢F检定 除了t检定外,我们也常用F值来检定单变量多组平均数 是否颢着
10-5 单变量变异数分析范例
我们想了解不同年龄层 A组20 ~29岁,B组30 ~39岁,C组 40~49岁,对笔记型Bubble喜好程度是否有差异,随机抽取年 龄层各5个人,以1 – 10的分数请他们评分如下:

英语托福考试阅读试题

英语托福考试阅读试题

英语托福考试阅读试题英语托福考试阅读试题 Question 1-8 Both the number and the percentage of people in the United States involved in nonagricultural pursuits expanded rapidly during the half century following the Civil War,with some of the most dramatic increases occurring in the domains of transportation,manufacturing,and trade and distribution。

The development of the railroad and telegraph systems during the middle third of the nineteenth century led to significant improvements in the speed,volume,and regularity of shipments and communications,making possible a fundamental transformation in the production and distribution of goods。

In agriculture,the transformation was marked by the emergence of the grain elevators,the cotton presses,the warehouses,and the commodity exchanges that seemed to so many of the nation‘s farmers the visible sign of a vast conspiracy against them。

routine练习题

routine练习题

routine练习题一、词汇练习1. 选择正确的单词填空:1. I usually _______ to work bus.2. She _______ her homework every evening.A. doesB. doC. does not doD. doesn't do3. They _______ a movie last night.A. watchB. watchesC. watchedD. watching2. 选择正确的词组:1. I _______ (go, going) to the gym this morning.2. He _______ (be, is) late for school again.3. She _______ (do, does) her homework every day.3. 选择正确的形容词:1. This is a _______ (good, bad) book.2. She is a _______ (smart, silly) girl.3. The weather is very _______ (hot, cold) today.二、语法练习1. 选择正确的时态:1. I _______ (go, went) to the park yesterday.2. She _______ (be, was) happy when she received the gift.3. They _______ (do, did) their homework last night.2. 选择正确的语态:1. The teacher _______ (teach, is taught) Mr. Wang.2. The book _______ (write, is written) a famous author.3. The letter _______ (send, is sent) to her last week.3. 选择正确的连词:1. I _______ (go, am going) to the movies, _______ (because, because of) I have free time.2. She _______ (like, likes) coffee, _______ (but, but) she doesn't like tea.3. I _______ (finish, finished) my homework, _______ (so, so) I can go out now.三、阅读理解1. 阅读短文,回答问题:1. What is the main idea of the passage?2. Who is the main character in the story?3. What happens at the end of the passage?2. 阅读文章,判断正误:1. The story is about a boy who goes to the park every weekend.2. The boy meets his friends at the park and they play games together.3. The boy goes home after playing games with his friends.3. 阅读文章,找出关键信息:1. What is the author's favorite color?2. Why does the author like this color?3. What does the author think about other colors?四、写作练习1. 介绍动物的名字和种类。

重要哲学术语英汉对照

重要哲学术语英汉对照

重要哲学术语英汉对照——转载自《当代英美哲学概论》a priori瞐 posteriori distinction 先验-后验的区分abstract ideas 抽象理念abstract objects 抽象客体ad hominem argument 谬误论证alienation/estrangement 异化,疏离altruism 利他主义analysis 分析analytic瞫ynthetic distinction 分析-综合的区分aporia 困惑argument from design 来自设计的论证artificial intelligence (AI) 人工智能association of ideas 理念的联想autonomy 自律axioms 公理Categorical Imperative 绝对命令categories 范畴Category mistake 范畴错误causal theory of reference 指称的因果论causation 因果关系certainty 确定性chaos theory 混沌理论class 总纲、类clearness and distinctness 清楚与明晰cogito ergo sum 我思故我在concept 概念consciousness 意识consent 同意consequentialism 效果论conservative 保守的consistency 一致性,相容性constructivism 建构主义contents of consciousness 意识的内容contingent瞡ecessary distinction 偶然-必然的区分 continuum 连续体continuum hypothesis 连续性假说contradiction 矛盾(律)conventionalism 约定论counterfactual conditional 反事实的条件句criterion 准则,标准critique 批判,批评Dasein 此在,定在deconstruction 解构主义defeasible 可以废除的definite description 限定摹状词deontology 义务论dialectic 辩证法didactic 说教的dualism 二元论egoism 自我主义、利己主义eliminative materialism 消除性的唯物主义 empiricism 经验主义Enlightenment 启蒙运动(思想)entailment 蕴含essence 本质ethical intuition 伦理直观ethical naturalism 伦理的自然主义eudaimonia 幸福主义event 事件、事变evolutionary epistemology 进化认识论expert system 专门体系explanation 解释fallibilism 谬误论family resemblance 家族相似fictional entities 虚构的实体first philosophy 第一哲学form of life 生活形式formal 形式的foundationalism 基础主义free will and determinism 自由意志和决定论 function 函项(功能)function explanation 功能解释good 善happiness 幸福hedonism 享乐主义hermeneutics 解释学(诠释学,释义学)historicism 历史论(历史主义)holism 整体论iconographic 绘画idealism 理念论ideas 理念identity 同一性illocutionary act 以言行事的行为imagination 想象力immaterical substance 非物质实体immutable 不变的、永恒的individualism 个人主义(个体主义)induction 归纳inference 推断infinite regress 无限回归intensionality 内涵性intentionality 意向性irreducible 不可还原的Leibniz餾 Law 莱布尼茨法则logical atomism 逻辑原子主义logical positivism 逻辑实证主义logomachy 玩弄词藻的争论material biconditional 物质的双向制约materialism 唯物论(唯物主义)maxim 箴言,格言method 方法methodologica 方法论的model 样式modern 现代的modus ponens and modus tollens 肯定前件和否定后件 natural selection 自然选择necessary 必然的neutral monism 中立一无论nominalism 唯名论non睧uclidean geometry 非欧几里德几何non瞞onotonic logics 非单一逻辑Ockham餜azor 奥卡姆剃刀omnipotence and omniscience 全能和全知ontology 本体论(存有学)operator 算符(或算子)paradox 悖论perception 知觉phenomenology 现象学picture theory of meaning 意义的图像说pluralism 多元论polis 城邦possible world 可能世界postmodernism 后现代主义prescriptive statement 规定性陈述presupposition 预设primary and secondary qualities 第一性的质和第二性的质 principle of non瞔ontradiction 不矛盾律proposition 命题quantifier 量词quantum mechanics 量子力学rational numbers 有理数real number 实数realism 实在论reason 理性,理智recursive function 循环函数reflective equilibrium 反思的均衡relativity (theory of) 相对(论)rights 权利rigid designator严格的指称词Rorschach test 相对性(相对论)rule 规则rule utilitarianism 功利主义规则Russell餾 paradox 罗素悖论sanctions 制发scope 范围,限界semantics 语义学sense data 感觉材料,感觉资料set 集solipsism 唯我论social contract 社会契约subjective瞣bjective distinction 主客区分 sublation 扬弃substance 实体,本体sui generis 特殊的,独特性supervenience 偶然性syllogism 三段论things瞚n瞭hemselves 物自体thought 思想thought experiment 思想实验three瞯alued logic 三值逻辑transcendental 先验的truth 真理truth function 真值函项understanding 理解universals 共相,一般,普遍verfication principle 证实原则versimilitude 逼真性vicious regress 恶性回归Vienna Circle 维也纳学派virtue 美德注释计量经济学中英对照词汇(continuous)2007年8月23日,22:02:47 | mindreader计量经济学中英对照词汇(continuous)K-Means Cluster逐步聚类分析K means method, 逐步聚类法Kaplan-Meier, 评估事件的时间长度Kaplan-Merier chart, Kaplan-Merier图Kendall's rank correlation, Kendall等级相关Kinetic, 动力学Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验Kurtosis, 峰度Lack of fit, 失拟Ladder of powers, 幂阶梯Lag, 滞后Large sample, 大样本Large sample test, 大样本检验Latin square, 拉丁方Latin square design, 拉丁方设计Leakage, 泄漏Least favorable configuration, 最不利构形Least favorable distribution, 最不利分布Least significant difference, 最小显著差法Least square method, 最小二乘法Least Squared Criterion,最小二乘方准则Least-absolute-residuals estimates, 最小绝对残差估计Least-absolute-residuals fit, 最小绝对残差拟合Least-absolute-residuals line, 最小绝对残差线Legend, 图例L-estimator, L估计量L-estimator of location, 位置L估计量L-estimator of scale, 尺度L估计量Level, 水平Leveage Correction,杠杆率校正Life expectance, 预期期望寿命Life table, 寿命表Life table method, 生命表法Light-tailed distribution, 轻尾分布Likelihood function, 似然函数Likelihood ratio, 似然比line graph, 线图Linear correlation, 直线相关Linear equation, 线性方程Linear programming, 线性规划Linear regression, 直线回归Linear Regression, 线性回归Linear trend, 线性趋势Loading, 载荷Location and scale equivariance, 位置尺度同变性Location equivariance, 位置同变性Location invariance, 位置不变性Location scale family, 位置尺度族Log rank test, 时序检验Logarithmic curve, 对数曲线Logarithmic normal distribution, 对数正态分布Logarithmic scale, 对数尺度Logarithmic transformation, 对数变换Logic check, 逻辑检查Logistic distribution, 逻辑斯特分布Logit transformation, Logit转换LOGLINEAR, 多维列联表通用模型Lognormal distribution, 对数正态分布Lost function, 损失函数Low correlation, 低度相关Lower limit, 下限Lowest-attained variance, 最小可达方差LSD, 最小显著差法的简称Lurking variable, 潜在变量Main effect, 主效应Major heading, 主辞标目Marginal density function, 边缘密度函数Marginal probability, 边缘概率Marginal probability distribution, 边缘概率分布Matched data, 配对资料Matched distribution, 匹配过分布Matching of distribution, 分布的匹配Matching of transformation, 变换的匹配Mathematical expectation, 数学期望Mathematical model, 数学模型Maximum L-estimator, 极大极小L 估计量Maximum likelihood method, 最大似然法Mean, 均数Mean squares between groups, 组间均方Mean squares within group, 组内均方Means (Compare means), 均值-均值比较Median, 中位数Median effective dose, 半数效量Median lethal dose, 半数致死量Median polish, 中位数平滑Median test, 中位数检验Minimal sufficient statistic, 最小充分统计量Minimum distance estimation, 最小距离估计Minimum effective dose, 最小有效量Minimum lethal dose, 最小致死量Minimum variance estimator, 最小方差估计量MINITAB, 统计软件包Minor heading, 宾词标目Missing data, 缺失值Model specification, 模型的确定Modeling Statistics , 模型统计Models for outliers, 离群值模型Modifying the model, 模型的修正Modulus of continuity, 连续性模Morbidity, 发病率Most favorable configuration, 最有利构形MSC(多元散射校正)Multidimensional Scaling (ASCAL), 多维尺度/多维标度Multinomial Logistic Regression , 多项逻辑斯蒂回归Multiple comparison, 多重比较Multiple correlation , 复相关Multiple covariance, 多元协方差Multiple linear regression, 多元线性回归Multiple response , 多重选项Multiple solutions, 多解Multiplication theorem, 乘法定理Multiresponse, 多元响应Multi-stage sampling, 多阶段抽样Multivariate T distribution, 多元T分布Mutual exclusive, 互不相容Mutual independence, 互相独立Natural boundary, 自然边界Natural dead, 自然死亡Natural zero, 自然零Negative correlation, 负相关Negative linear correlation, 负线性相关Negatively skewed, 负偏Newman-Keuls method, q检验NK method, q检验No statistical significance, 无统计意义Nominal variable, 名义变量Nonconstancy of variability, 变异的非定常性Nonlinear regression, 非线性相关Nonparametric statistics, 非参数统计Nonparametric test, 非参数检验Nonparametric tests, 非参数检验Normal deviate, 正态离差Normal distribution, 正态分布Normal equation, 正规方程组Normal P-P, 正态概率分布图Normal Q-Q, 正态概率单位分布图Normal ranges, 正常范围Normal value, 正常值Normalization 归一化Nuisance parameter, 多余参数/讨厌参数Null hypothesis, 无效假设Numerical variable, 数值变量Objective function, 目标函数Observation unit, 观察单位Observed value, 观察值One sided test, 单侧检验One-way analysis of variance, 单因素方差分析Oneway ANOVA , 单因素方差分析Open sequential trial, 开放型序贯设计Optrim, 优切尾Optrim efficiency, 优切尾效率Order statistics, 顺序统计量Ordered categories, 有序分类Ordinal logistic regression , 序数逻辑斯蒂回归Ordinal variable, 有序变量Orthogonal basis, 正交基Orthogonal design, 正交试验设计Orthogonality conditions, 正交条件ORTHOPLAN, 正交设计Outlier cutoffs, 离群值截断点Outliers, 极端值OVERALS , 多组变量的非线性正规相关Overshoot, 迭代过度Paired design, 配对设计Paired sample, 配对样本Pairwise slopes, 成对斜率Parabola, 抛物线Parallel tests, 平行试验Parameter, 参数Parametric statistics, 参数统计Parametric test, 参数检验Pareto, 直条构成线图(又称佩尔托图)Partial correlation, 偏相关Partial regression, 偏回归Partial sorting, 偏排序Partials residuals, 偏残差Pattern, 模式PCA(主成分分析)Pearson curves, 皮尔逊曲线Peeling, 退层Percent bar graph, 百分条形图Percentage, 百分比Percentile, 百分位数Percentile curves, 百分位曲线Periodicity, 周期性Permutation, 排列P-estimator, P估计量Pie graph, 构成图,饼图Pitman estimator, 皮特曼估计量Pivot, 枢轴量Planar, 平坦Planar assumption, 平面的假设PLANCARDS, 生成试验的计划卡PLS(偏最小二乘法)Point estimation, 点估计Poisson distribution, 泊松分布Polishing, 平滑Polled standard deviation, 合并标准差Polled variance, 合并方差Polygon, 多边图Polynomial, 多项式Polynomial curve, 多项式曲线Population, 总体Population attributable risk, 人群归因危险度Positive correlation, 正相关Positively skewed, 正偏Posterior distribution, 后验分布Power of a test, 检验效能Precision, 精密度Predicted value, 预测值Preliminary analysis, 预备性分析Principal axis factoring,主轴因子法Principal component analysis, 主成分分析Prior distribution, 先验分布Prior probability, 先验概率Probabilistic model, 概率模型probability, 概率Probability density, 概率密度Product moment, 乘积矩/协方差Pro, 截面迹图Proportion, 比/构成比Proportion allocation in stratified random sampling, 按比例分层随机抽样Proportionate, 成比例Proportionate sub-class numbers, 成比例次级组含量Prospective study, 前瞻性调查Proximities, 亲近性Pseudo F test, 近似F检验Pseudo model, 近似模型Pseudosigma, 伪标准差Purposive sampling, 有目的抽样QR decomposition, QR分解Quadratic approximation, 二次近似Qualitative classification, 属性分类Qualitative method, 定性方法Quantile-quantile plot, 分位数-分位数图/Q-Q图Quantitative analysis, 定量分析Quartile, 四分位数Quick Cluster, 快速聚类Radix sort, 基数排序Random allocation, 随机化分组Random blocks design, 随机区组设计Random event, 随机事件Randomization, 随机化Range, 极差/全距Rank correlation, 等级相关Rank sum test, 秩和检验Rank test, 秩检验Ranked data, 等级资料Rate, 比率Ratio, 比例Raw data, 原始资料Raw residual, 原始残差Rayleigh's test, 雷氏检验Rayleigh's Z, 雷氏Z值Reciprocal, 倒数Reciprocal transformation, 倒数变换Recording, 记录Redescending estimators, 回降估计量Reducing dimensions, 降维Re-expression, 重新表达Reference set, 标准组Region of acceptance, 接受域Regression coefficient, 回归系数Regression sum of square, 回归平方和Rejection point, 拒绝点Relative dispersion, 相对离散度Relative number, 相对数Reliability, 可靠性Reparametrization, 重新设置参数Replication, 重复Report Summaries, 报告摘要Residual sum of square, 剩余平方和residual variance (剩余方差)Resistance, 耐抗性Resistant line, 耐抗线Resistant technique, 耐抗技术R-estimator of location, 位置R估计量R-estimator of scale, 尺度R估计量Retrospective study, 回顾性调查Ridge trace, 岭迹Ridit analysis, Ridit分析Rotation, 旋转Rounding, 舍入Row, 行Row effects, 行效应Row factor, 行因素RXC table, RXC表Sample, 样本Sample regression coefficient, 样本回归系数Sample size, 样本量Sample standard deviation, 样本标准差Sampling error, 抽样误差SAS(Statistical analysis system , SAS统计软件包Scale, 尺度/量表Scatter diagram, 散点图Schematic plot, 示意图/简图Score test, 计分检验Screening, 筛检SEASON, 季节分析Second derivative, 二阶导数Second principal component, 第二主成分SEM (Structural equation modeling), 结构化方程模型Semi-logarithmic graph, 半对数图Semi-logarithmic paper, 半对数格纸Sensitivity curve, 敏感度曲线Sequential analysis, 贯序分析Sequence, 普通序列图Sequential data set, 顺序数据集Sequential design, 贯序设计Sequential method, 贯序法Sequential test, 贯序检验法Serial tests, 系列试验Short-cut method, 简捷法Sigmoid curve, S形曲线Sign function, 正负号函数Sign test, 符号检验Signed rank, 符号秩Significant Level, 显著水平Significance test, 显著性检验Significant figure, 有效数字Simple cluster sampling, 简单整群抽样Simple correlation, 简单相关Simple random sampling, 简单随机抽样Simple regression, 简单回归simple table, 简单表Sine estimator, 正弦估计量Single-valued estimate, 单值估计Singular matrix, 奇异矩阵Skewed distribution, 偏斜分布Skewness, 偏度Slash distribution, 斜线分布Slope, 斜率Smirnov test, 斯米尔诺夫检验Source of variation, 变异来源Spearman rank correlation, 斯皮尔曼等级相关Specific factor, 特殊因子Specific factor variance, 特殊因子方差Spectra , 频谱Spherical distribution, 球型正态分布Spread, 展布SPSS(Statistical package for the social science), SPSS统计软件包Spurious correlation, 假性相关Square root transformation, 平方根变换Stabilizing variance, 稳定方差Standard deviation, 标准差Standard error, 标准误Standard error of difference, 差别的标准误Standard error of estimate, 标准估计误差Standard error of rate, 率的标准误Standard normal distribution, 标准正态分布Standardization, 标准化Starting value, 起始值Statistic, 统计量Statistical control, 统计控制Statistical graph, 统计图Statistical inference, 统计推断Statistical table, 统计表Steepest descent, 最速下降法Stem and leaf display, 茎叶图Step factor, 步长因子Stepwise regression, 逐步回归Storage, 存Strata, 层(复数)Stratified sampling, 分层抽样Stratified sampling, 分层抽样Strength, 强度Stringency, 严密性Structural relationship, 结构关系Studentized residual, 学生化残差/t化残差Sub-class numbers, 次级组含量Subdividing, 分割Sufficient statistic, 充分统计量Sum of products, 积和Sum of squares, 离差平方和Sum of squares about regression, 回归平方和Sum of squares between groups, 组间平方和Sum of squares of partial regression, 偏回归平方和Sure event, 必然事件Survey, 调查Survival, 生存分析Survival rate, 生存率Suspended root gram, 悬吊根图Symmetry, 对称Systematic error, 系统误差Systematic sampling, 系统抽样Tags, 标签Tail area, 尾部面积Tail length, 尾长Tail weight, 尾重Tangent line, 切线Target distribution, 目标分布Taylor series, 泰勒级数Test(检验)Test of linearity, 线性检验Tendency of dispersion, 离散趋势Testing of hypotheses, 假设检验Theoretical frequency, 理论频数Time series, 时间序列Tolerance interval, 容忍区间Tolerance lower limit, 容忍下限Tolerance upper limit, 容忍上限Torsion, 扰率Total sum of square, 总平方和Total variation, 总变异Transformation, 转换Treatment, 处理Trend, 趋势Trend of percentage, 百分比趋势Trial, 试验Trial and error method, 试错法Tuning constant, 细调常数Two sided test, 双向检验Two-stage least squares, 二阶最小平方Two-stage sampling, 二阶段抽样Two-tailed test, 双侧检验Two-way analysis of variance, 双因素方差分析Two-way table, 双向表Type I error, 一类错误/α错误Type II error, 二类错误/β错误UMVU, 方差一致最小无偏估计简称Unbiased estimate, 无偏估计Unconstrained nonlinear regression , 无约束非线性回归Unequal subclass number, 不等次级组含量Ungrouped data, 不分组资料Uniform coordinate, 均匀坐标Uniform distribution, 均匀分布Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计Unit, 单元Unordered categories, 无序分类Unweighted least squares, 未加权最小平方法Upper limit, 上限Upward rank, 升秩Vague concept, 模糊概念Validity, 有效性VARCOMP (Variance component estimation), 方差元素估计Variability, 变异性Variable, 变量Variance, 方差Variation, 变异Varimax orthogonal rotation, 方差最大正交旋转Volume of distribution, 容积W test, W检验Weibull distribution, 威布尔分布Weight, 权数Weighted Chi-square test, 加权卡方检验/Cochran检验Weighted linear regression method, 加权直线回归Weighted mean, 加权平均数Weighted mean square, 加权平均方差Weighted sum of square, 加权平方和Weighting coefficient, 权重系数Weighting method, 加权法W-estimation, W估计量W-estimation of location, 位置W估计量Width, 宽度Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验Wild point, 野点/狂点Wild value, 野值/狂值Winsorized mean, 缩尾均值Withdraw, 失访Youden's index, 尤登指数Z test, Z检验Zero correlation, 零相关Z-transformation, Z变换注释。

2019-2020年人教版高中英语必修5、选修6必修5复习巩固第四十五篇.doc

2019-2020年人教版高中英语必修5、选修6必修5复习巩固第四十五篇.doc

2019-2020年人教版高中英语必修5、选修6必修5复习巩固第四十五篇4第1题【单选题】To keep healthy, my father _________ o gging as a regular form of exercise after work・A、took upB、turned upC、brought upD、set up【答案】:A【解析】:take up意为“从事;开始做某事";turn up意为“出现";bring up意为"提出;养育";set up意为"建立;创建".句意:为保持健康r我父亲把下班后慢跑作为一种常用的锻炼方式。

【点评】考童动词短融析。

由同一个单词组成的不同短语意义不同,应注意区分记忆。

4第2题【单选题】After the stranger left, suspicion(猜疑)_________ among the villagers・A、roseB、aroseC、raisedD、lifted【答案】:B【解析】:【分析】句意:另阶陌生人离开之后r村民之间的猜疑上升了. arise “产生,出现"f符合题意。

rise指主语自身移向较髙的位置,往4曲自然界的日、月等的”升起” ;raise指輙物从低处升到高处;lifts用体力或机械力举起某物。

选B.【点评】考查动词辨析,区分rise , arise , raise「lift的含义和应用。

4第3题【单选题】For breakfast he only drinks juice from fresh fruit _________ on his own farm.A、grownB、being grownC、to get grownA、 B、CD 、to grow【答案】:【解析】:【分析】句意:早餐他只喝了自家农场中的新鲜水果榨的果汁。

fruit grown on his own farm 他自己农场种植的水果。

spss中一般线性模型ppt课件

spss中一般线性模型ppt课件

例如,因素有Light(F)、Device(F)、Target(F),若要 求模型中包括变量Light与Device交互效应。 首先定义效应类型为Interactin, 然后在Factors&Covariates框内的变量表中,用鼠标单击 Device变量使其背景改变颜色,再用鼠标单击变量Light变 量使其背景改变颜色;单击Build Term(s)栏内残数框的 箭头按钮,一个交互效应出现在Model框中。模型增加了一 个交互效应项:Device*Light。

GLM可完成多自变量、多水平、多因变量、重复测 量方差分析以及协方差分析等。
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Univariate(单因变量方差分析)基本过程
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1 主对话框

Dependent Variable:因变量
Fixed Facter: 固定因子,所有可能的水 平都出现在样本中,如分组等 Random Facter: 随机因子,所有可能 的取值并不都在样本中出现,如观察个 体 Covariates:协变量,协方差分析时用
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2.3 Plots按钮

Factor:主对话框中所选因素 变量名; Horizontal:横坐标框 Separate Lines:确定分线变量 Separate Plots:确定分图变量

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2.4 Post Hoc按钮

均数多重比较(事后检验)
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2.5 Save按钮(选择保存运算值)



WLS Weight: WLS权重。用于加权最 小二乘分析。
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2 功能按钮


Model:分析模型
Contrast:对照方法 Plots:分布图形 Post Hoc:多重比较 Save:保存运算值

《统计词汇中英文对照》

《统计词汇中英文对照》

《统计词汇中英文对照》Effect, 实验效应Eigenvalue, 特征值Eigenvector, 特征向量Ellipse, 椭圆Empirical distribution, 经验分布Empirical probability, 经验概率单位Enumeration data, 计数资料Equal sun-class number, 相等次级组含量Equally likely, 等可能Equivariance, 同变性Error, 误差/错误Error of estimate, 估计误差Error type I, 第一类错误Error type II, 第二类错误Estimand, 被估量Estimated error mean squares, 估计误差均方Estimated error sum of squares, 估计误差平方与Euclidean distance, 欧式距离Event, 事件Event, 事件Exceptional data point, 特殊数据点Expectation plane, 期望平面Expectation surface, 期望曲面Expected values, 期望值Experiment, 实验Experimental sampling, 试验抽样Experimental unit, 试验单位Explanatory variable, 说明变量Exploratory data analysis, 探索性数据分析Explore Summarize, 探索-摘要Exponential curve, 指数曲线Exponential growth, 指数式增长EXSMOOTH, 指数平滑方法Extended fit, 扩充拟合Extra parameter, 附加参数Extrapolation, 外推法Extreme observation, 末端观测值Extremes, 极端值/极值F distribution, F分布F test, F检验Factor, 因素/因子Factor analysis, 因子分析Factor Analysis, 因子分析Factor score, 因子得分Factorial, 阶乘Factorial design, 析因试验设计False negative, 假阴性False negative error, 假阴性错误Family of distributions, 分布族Family of estimators, 估计量族Fanning, 扇面Fatality rate, 病死率Field investigation, 现场调查Field survey, 现场调查Finite population, 有限总体Finite-sample, 有限样本First derivative, 一阶导数First principal component, 第一主成分First quartile, 第一四分位数Fisher information, 费雪信息量Fitted value, 拟合值Fitting a curve, 曲线拟合Fixed base, 定基Fluctuation, 随机起伏Forecast, 预测Four fold table, 四格表Fourth, 四分点Fraction blow, 左侧比率Fractional error, 相对误差Frequency, 频率Frequency polygon, 频数多边图Frontier point, 界限点Function relationship, 泛函关系Gamma distribution, 伽玛分布Gauss increment, 高斯增量Gaussian distribution, 高斯分布/正态分布Gauss-Newton increment, 高斯-牛顿增量General census, 全面普查GENLOG (Generalized liner models), 广义线性模型Geometric mean, 几何平均数Gini's mean difference, 基尼均差GLM (General liner models), 通用线性模型Goodness of fit, 拟与优度/配合度Gradient of determinant, 行列式的梯度Graeco-Latin square, 希腊拉丁方Grand mean, 总均值Gross errors, 重大错误Gross-error sensitivity, 大错敏感度Group averages, 分组平均Grouped data, 分组资料Guessed mean, 假定平均数Half-life, 半衰期Hampel M-estimators, 汉佩尔M估计量Happenstance, 偶然事件Harmonic mean, 调与均数Hazard function, 风险均数Hazard rate, 风险率Heading, 标目Heavy-tailed distribution, 重尾分布Hessian array, 海森立体阵Heterogeneity, 不一致质Heterogeneity of variance, 方差不齐Hierarchical classification, 组内分组Hierarchical clustering method, 系统聚类法High-leverage point, 高杠杆率点HILOGLINEAR, 多维列联表的层次对数线性模型Hinge, 折叶点Histogram, 直方图Historical cohort study, 历史性队列研究Holes, 空洞HOMALS, 多重响应分析Homogeneity of variance, 方差齐性Homogeneity test, 齐性检验Huber M-estimators, 休伯M估计量Hyperbola, 双曲线Hypothesis testing, 假设检验Hypothetical universe, 假设总体Impossible event, 不可能事件Independence, 独立性Independent variable, 自变量Index, 指标/指数Indirect standardization, 间接标准化法Individual, 个体Inference band, 推断带Infinite population, 无限总体Infinitely great, 无穷大Infinitely small, 无穷小Influence curve, 影响曲线Information capacity, 信息容量Initial condition, 初始条件Initial estimate, 初始估计值Initial level, 最初水平Interaction, 交互作用Interaction terms, 交互作用项Intercept, 截距Interpolation, 内插法Interquartile range, 四分位距Interval estimation, 区间估计Intervals of equal probability, 等概率区间Intrinsic curvature, 固有曲率Invariance, 不变性Inverse matrix, 逆矩阵Inverse probability, 逆概率Inverse sine transformation, 反正弦变换Iteration, 迭代Jacobian determinant, 雅可比行列式Joint distribution function, 分布函数Joint probability, 联合概率Joint probability distribution, 联合概率分布K means method, 逐步聚类法Kaplan-Meier, 评估事件的时间长度Kaplan-Merier chart, Kaplan-Merier图Kendall's rank correlation, Kendall等级有关Kinetic, 动力学Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩与检验/H 检验Kurtosis, 峰度Lack of fit, 失拟Ladder of powers, 幂阶梯Lag, 滞后Large sample, 大样本Large sample test, 大样本检验Latin square, 拉丁方Latin square design, 拉丁方设计Leakage, 泄漏Least favorable configuration, 最不利构形Least favorable distribution, 最不利分布Least significant difference, 最小显著差法Least square method, 最小二乘法Least-absolute-residuals estimates, 最小绝对残差估计Least-absolute-residuals fit, 最小绝对残差拟合Least-absolute-residuals line, 最小绝对残差线Legend, 图例L-estimator, L估计量L-estimator of location, 位置L估计量L-estimator of scale, 尺度L估计量Level, 水平Life expectance, 预期期望寿命Life table, 寿命表Life table method, 生命表法Light-tailed distribution, 轻尾分布Likelihood function, 似然函数Likelihood ratio, 似然比line graph, 线图Linear correlation, 直线有关Linear equation, 线性方程Linear programming, 线性规划Linear regression, 直线回归Linear Regression, 线性回归Linear trend, 线性趋势Loading, 载荷Location and scale equivariance, 位置尺度同变性Location equivariance, 位置同变性Location invariance, 位置不变性Location scale family, 位置尺度族Log rank test, 时序检验Logarithmic curve, 对数曲线Logarithmic normal distribution, 对数正态分布Logarithmic scale, 对数尺度Logarithmic transformation, 对数变换Logic check, 逻辑检查Logistic distribution, 逻辑斯特分布Logit transformation, Logit转换LOGLINEAR, 多维列联表通用模型Lognormal distribution, 对数正态分布Lost function, 缺失函数Low correlation, 低度有关Lower limit, 下限Lowest-attained variance, 最小可达方差LSD, 最小显著差法的简称Lurking variable, 潜在变量Main effect, 主效应Major heading, 主辞标目Marginal density function, 边缘密度函数Marginal probability, 边缘概率Marginal probability distribution, 边缘概率分布Matched data, 配对资料Matched distribution, 匹配过分布Matching of distribution, 分布的匹配Matching of transformation, 变换的匹配Mathematical expectation, 数学期望Mathematical model, 数学模型Maximum L-estimator, 极大极小L 估计量Maximum likelihood method, 最大似然法Mean, 均数Mean squares between groups, 组间均方Mean squares within group, 组内均方Means (Compare means), 均值-均值比较Median, 中位数Median effective dose, 半数效量Median lethal dose, 半数致死量Median polish, 中位数平滑Median test, 中位数检验Minimal sufficient statistic, 最小充分统计量Minimum distance estimation, 最小距离估计Minimum effective dose, 最小有效量Minimum lethal dose, 最小致死量Minimum variance estimator, 最小方差估计量MINITAB, 统计软件包Minor heading, 宾词标目Missing data, 缺失值Model specification, 模型的确定Modeling Statistics , 模型统计Models for outliers, 离群值模型Modifying the model, 模型的修正Modulus of continuity, 连续性模Morbidity, 发病率Most favorable configuration, 最有利构形Multidimensional Scaling (ASCAL), 多维尺度/多维标度Multinomial Logistic Regression , 多项逻辑斯蒂回归Multiple comparison, 多重比较Multiple correlation , 复有关Multiple covariance, 多元协方差Multiple linear regression, 多元线性回归Multiple response , 多重选项Multiple solutions, 多解Multiplication theorem, 乘法定理Multiresponse, 多元响应Multi-stage sampling, 多阶段抽样Multivariate T distribution, 多元T分布Mutual exclusive, 互不相容Mutual independence, 互相独立Natural boundary, 自然边界Natural dead, 自然死亡Natural zero, 自然零Negative correlation, 负有关Negative linear correlation, 负线性有关Negatively skewed, 负偏Newman-Keuls method, q检验NK method, q检验No statistical significance, 无统计意义Nominal variable, 名义变量Nonconstancy of variability, 变异的非定常性Nonlinear regression, 非线性有关Nonparametric statistics, 非参数统计Nonparametric test, 非参数检验Nonparametric tests, 非参数检验Normal deviate, 正态离差Normal distribution, 正态分布Normal equation, 正规方程组Normal ranges, 正常范围Normal value, 正常值Nuisance parameter, 多余参数/讨厌参数Null hypothesis, 无效假设Numerical variable, 数值变量Objective function, 目标函数Observation unit, 观察单位Observed value, 观察值One sided test, 单侧检验One-way analysis of variance, 单因素方差分析Oneway ANOVA , 单因素方差分析Open sequential trial, 开放型序贯设计Optrim, 优切尾Optrim efficiency, 优切尾效率Order statistics, 顺序统计量Ordered categories, 有序分类Ordinal logistic regression , 序数逻辑斯蒂回归Ordinal variable, 有序变量Orthogonal basis, 正交基Orthogonal design, 正交试验设计Orthogonality conditions, 正交条件ORTHOPLAN, 正交设计Outlier cutoffs, 离群值截断点Outliers, 极端值OVERALS , 多组变量的非线性正规有关Overshoot, 迭代过度Paired design, 配对设计Paired sample, 配对样本Pairwise slopes, 成对斜率Parabola, 抛物线Parallel tests, 平行试验Parameter, 参数Parametric statistics, 参数统计Parametric test, 参数检验Partial correlation, 偏有关Partial regression, 偏回归Partial sorting, 偏排序Partials residuals, 偏残差Pattern, 模式Pearson curves, 皮尔逊曲线Peeling, 退层Percent bar graph, 百分条形图Percentage, 百分比Percentile, 百分位数Percentile curves, 百分位曲线Periodicity, 周期性Permutation, 排列P-estimator, P估计量Pie graph, 饼图Pitman estimator, 皮特曼估计量Pivot, 枢轴量Planar, 平坦Planar assumption, 平面的假设PLANCARDS, 生成试验的计划卡Point estimation, 点估计Poisson distribution, 泊松分布Polishing, 平滑Polled standard deviation, 合并标准差Polled variance, 合并方差Polygon, 多边图Polynomial, 多项式Polynomial curve, 多项式曲线Population, 总体Population attributable risk, 人群归因危险度Positive correlation, 正有关Positively skewed, 正偏Posterior distribution, 后验分布Power of a test, 检验效能Precision, 精密度Predicted value, 预测值Preliminary analysis, 预备性分析Principal component analysis, 主成分分析Prior distribution, 先验分布Prior probability, 先验概率Probabilistic model, 概率模型probability, 概率Probability density, 概率密度Product moment, 乘积矩/协方差Profile trace, 截面迹图Proportion, 比/构成比Proportion allocation in stratified random sampling, 按比例分层随机抽样Proportionate, 成比例Proportionate sub-class numbers, 成比例次级组含量Prospective study, 前瞻性调查Proximities, 亲近性Pseudo F test, 近似F检验Pseudo model, 近似模型Pseudosigma, 伪标准差Purposive sampling, 有目的抽样QR decomposition, QR分解Quadratic approximation, 二次近似Qualitative classification, 属性分类Qualitative method, 定性方法Quantile-quantile plot, 分位数-分位数图/Q-Q图Quantitative analysis, 定量分析Quartile, 四分位数Quick Cluster, 快速聚类Radix sort, 基数排序Random allocation, 随机化分组Random blocks design, 随机区组设计Random event, 随机事件Randomization, 随机化Range, 极差/全距Rank correlation, 等级有关Rank sum test, 秩与检验Rank test, 秩检验Ranked data, 等级资料Rate, 比率Ratio, 比例Raw data, 原始资料Raw residual, 原始残差Rayleigh's test, 雷氏检验Rayleigh's Z, 雷氏Z值Reciprocal, 倒数Reciprocal transformation, 倒数变换Recording, 记录Redescending estimators, 回降估计量Reducing dimensions, 降维Re-expression, 重新表达Reference set, 标准组Region of acceptance, 同意域Regression coefficient, 回归系数Regression sum of square, 回归平方与Rejection point, 拒绝点Relative dispersion, 相对离散度Relative number, 相对数Reliability, 可靠性Reparametrization, 重新设置参数Replication, 重复Report Summaries, 报告摘要Residual sum of square, 剩余平方与Resistance, 耐抗性Resistant line, 耐抗线Resistant technique, 耐抗技术R-estimator of location, 位置R估计量R-estimator of scale, 尺度R估计量Retrospective study, 回顾性调查Ridge trace, 岭迹Ridit analysis, Ridit分析Rotation, 旋转Rounding, 舍入Row, 行Row effects, 行效应Row factor, 行因素RXC table, RXC表Sample, 样本Sample regression coefficient, 样本回归系数Sample size, 样本量Sample standard deviation, 样本标准差Sampling error, 抽样误差SAS(Statistical analysis system ), SAS统计软件包Scale, 尺度/量表Scatter diagram, 散点图Schematic plot, 示意图/简图Score test, 计分检验Screening, 筛检SEASON, 季节分析Second derivative, 二阶导数Second principal component, 第二主成分SEM (Structural equation modeling), 结构化方程模型Semi-logarithmic graph, 半对数图Semi-logarithmic paper, 半对数格纸Sensitivity curve, 敏感度曲线Sequential analysis, 贯序分析Sequential data set, 顺序数据集Sequential design, 贯序设计Sequential method, 贯序法Sequential test, 贯序检验法Serial tests, 系列试验Short-cut method, 简捷法Sigmoid curve, S形曲线Sign function, 正负号函数Sign test, 符号检验Signed rank, 符号秩Significance test, 显著性检验Significant figure, 有效数字Simple cluster sampling, 简单整群抽样Simple correlation, 简单有关Simple random sampling, 简单随机抽样Simple regression, 简单回归simple table, 简单表Sine estimator, 正弦估计量Single-valued estimate, 单值估计Singular matrix, 奇异矩阵Skewed distribution, 偏斜分布Skewness, 偏度Slash distribution, 斜线分布Slope, 斜率Smirnov test, 斯米尔诺夫检验Source of variation, 变异来源Spearman rank correlation, 斯皮尔曼等级有关Specific factor, 特殊因子Specific factor variance, 特殊因子方差Spectra , 频谱Spherical distribution, 球型正态分布Spread, 展布SPSS(Statistical package for the social science), SPSS统计软件包Spurious correlation, 假性有关Square root transformation, 平方根变换Stabilizing variance, 稳固方差Standard deviation, 标准差Standard error, 标准误Standard error of difference, 差别的标准误Standard error of estimate, 标准估计误差Standard error of rate, 率的标准误Standard normal distribution, 标准正态分布Standardization, 标准化Starting value, 起始值Statistic, 统计量Statistical control, 统计操纵Statistical graph, 统计图Statistical inference, 统计推断Statistical table, 统计表Steepest descent, 最速下降法Stem and leaf display, 茎叶图Step factor, 步长因子Stepwise regression, 逐步回归Storage, 存Strata, 层(复数)Stratified sampling, 分层抽样Stratified sampling, 分层抽样Strength, 强度Stringency, 严密性Structural relationship, 结构关系Studentized residual, 学生化残差/t化残差Sub-class numbers, 次级组含量Subdividing, 分割Sufficient statistic, 充分统计量Sum of products, 积与Sum of squares, 离差平方与Sum of squares about regression, 回归平方与Sum of squares between groups, 组间平方与Sum of squares of partial regression, 偏回归平方与Sure event, 必定事件Survey, 调查Survival, 生存分析Survival rate, 生存率Suspended root gram, 悬吊根图Symmetry, 对称Systematic error, 系统误差Systematic sampling, 系统抽样Tags, 标签Tail area, 尾部面积Tail length, 尾长Tail weight, 尾重Tangent line, 切线Target distribution, 目标分布Taylor series, 泰勒级数Tendency of dispersion, 离散趋势Testing of hypotheses, 假设检验Theoretical frequency, 理论频数Time series, 时间序列Tolerance interval, 容忍区间Tolerance lower limit, 容忍下限Tolerance upper limit, 容忍上限Torsion, 扰率Total sum of square, 总平方与Total variation, 总变异Transformation, 转换Treatment, 处理Trend, 趋势Trend of percentage, 百分比趋势Trial, 试验Trial and error method, 试错法Tuning constant, 细调常数Two sided test, 双向检验Two-stage least squares, 二阶最小平方Two-stage sampling, 二阶段抽样Two-tailed test, 双侧检验Two-way analysis of variance, 双因素方差分析Two-way table, 双向表Type I error, 一类错误/α错误Type II error, 二类错误/β错误UMVU, 方差一致最小无偏估计简称Unbiased estimate, 无偏估计Unconstrained nonlinear regression , 无约束非线性回归Unequal subclass number, 不等次级组含量Ungrouped data, 不分组资料Uniform coordinate, 均匀坐标Uniform distribution, 均匀分布Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计Unit, 单元Unordered categories, 无序分类Upper limit, 上限Upward rank, 升秩Vague concept, 模糊概念Validity, 有效性VARCOMP (Variance component estimation), 方差元素估计Variability, 变异性Variable, 变量Variance, 方差Variation, 变异Varimax orthogonal rotation, 方差最大正交旋转Volume of distribution, 容积W test, W检验Weibull distribution, 威布尔分布Weight, 权数Weighted Chi-square test, 加权卡方检验/Cochran检验Weighted linear regression method, 加权直线回归Weighted mean, 加权平均数Weighted mean square, 加权平均方差Weighted sum of square, 加权平方与Weighting coefficient, 权重系数Weighting method, 加权法W-estimation, W估计量W-estimation of location, 位置W估计量Width, 宽度Wilcoxon paired test, 威斯康星配对法/配对符号秩与检验Wild point, 野点/狂点Wild value, 野值/狂值Winsorized mean, 缩尾均值Withdraw, 失访Youden's index, 尤登指数Z test, Z检验Zero correlation, 零有关Z-transformation, Z变换。

强的松预防一期梅毒青霉素治疗期间吉海反应的效果

强的松预防一期梅毒青霉素治疗期间吉海反应的效果

强的松预防一期梅毒青霉素治疗期间吉海反应的效果姚继兵【摘要】目的探讨强的松预防一期梅毒青霉素治疗期间吉海反应的效果.方法选择进行青霉素治疗的68例一期梅毒患者为研究对象,按照随机数表法将患者随机分为对照组与观察组,每组34例.对照组患者在青霉素治疗期间不使用药物预防吉海反应,观察组患者在青霉素治疗期间使用强的松预防吉海反应,对比2组患者的吉海反应发生率.结果观察组患者发生吉海反应表现有高热寒战1例(2.94%)、呼吸加快2例(5.88%)、头疼1例(2.94%);对照组患者发生吉海反应表现有高热寒战4例(11.76%)、呼吸加快3例(8.82%)、头疼2例(5.88%)、恶心呕吐1例(2.94%).观察组的吉海反应发生率为5.88%,显著低于对照组的17.65% (P <0.05).结论使用强的松能有效预防一期梅毒患者青霉素治疗期间的吉海反应.【期刊名称】《实用临床医药杂志》【年(卷),期】2019(023)009【总页数】3页(P89-91)【关键词】一期梅毒;强的松;吉海反应;青霉素【作者】姚继兵【作者单位】上海市浦东新区妇幼保健所,上海,201399【正文语种】中文【中图分类】R759.1梅毒是一种慢性传染病,由梅毒螺旋体引起,主要是通过间接性接触、直接性接触、胎盘传播以及输血进行传播[1], 会对患者的健康造成严重威胁。

梅毒的发病率有不断升高的趋势,因此若患者已经确诊梅毒需尽早治疗,大约90%的梅毒患者经正规治疗后能够痊愈,且越早治疗,疗效越好[2]。

青霉素是治疗梅毒最有效且最普遍的药物,但患者通常会出现吉海反应。

吉海反应又名梅毒后增剧反应,属于治疗梅毒过程中发生的急性不良反应,经常于初次给药后的几小时内发生[3-4], 临床症状表现为血压升高、寒战、恶心、发热、呕吐、相关淋巴结肿大、全身不适、头痛、心动过速以及原发疾病暂时性恶化等[5]。

分析吉海反应的发生原因,是因为青霉素造成梅毒螺旋体死亡,有大量的异种蛋白在血液中被释放,刺激机体导致发生变态反应,此外也可能由于人体对梅毒螺旋体内的毒素高度敏感造成[6]。

肝癌免疫细胞浸润模式及与预后的相关性分析

肝癌免疫细胞浸润模式及与预后的相关性分析

肝癌免疫细胞浸润模式及与预后的相关性分析程熠;吴莹莹;刘东伯;郭秋云【摘要】目的研究肝癌免疫细胞的浸润模式,探索免疫细胞浸润与预后的关系.方法从TCGA数据库下载肝细胞癌转录本数据及相关临床数据,通过Cibersort软件的反卷积法计算22种免疫细胞的占比.采用K-M生存分析Log-Rank法计算每种免疫细胞与生存的相关性.结果从TCGA数据库中得到基因转录本数据共424例,包含肝癌组织374例、正常肝组织50例.每个样本检测基因位点60483个,包含mRNA 19658个.数据校正后使用Cibersort软件\"反卷积法\"得到22种免疫细胞的占比数据,采用P<0.05筛选样本,得到肝细胞癌组织40例、正常肝组织2例.K-M生存分析显示活化的肥大细胞、未活化的自然杀伤细胞、嗜酸性粒细胞组成比例高者预后差,活化的自然杀伤细胞比例高者预后更好.结论肝癌中存在各类免疫细胞不同程度的浸润,浸润性免疫细胞可以作为影响肝癌患者预后的因素.【期刊名称】《华中科技大学学报(医学版)》【年(卷),期】2019(048)003【总页数】5页(P276-280)【关键词】肝癌;免疫细胞浸润;预后【作者】程熠;吴莹莹;刘东伯;郭秋云【作者单位】华中科技大学同济医学院附属同济医院肿瘤中心,武汉 430030;华中科技大学同济医学院附属同济医院肿瘤中心,武汉 430030;华中科技大学同济医学院附属同济医院肿瘤中心,武汉 430030;华中科技大学同济医学院附属同济医院肿瘤中心,武汉 430030【正文语种】中文【中图分类】R735.7肝癌是指原发于肝脏的恶性肿瘤,主要包括肝细胞癌(hepatocellular carcinoma,HCC)和肝内胆管癌(intrahepatic cholangiocarcinoma,ICC)两种组织学类型,其中肝细胞癌占70%~85%,本文中所提及肝癌均特指肝细胞癌。

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) 2νj + h 2
ν h −1 k −0
1 + e2πi(α2
k+ 1 ) 2
.
Formulas (15)-(17) give an explicit expression for Sm (N ) as a linear combination of the products of the form
ESTIMATES OF NEWMAN SUM OVER NUMBERS MULTIPLE OF A FIXED INTEGER
arXiv:0804.0144v6 [math.NT] 31 May 2008
VLADIMIR SHEVELEV Abstract. We prove that the ratio of the Newman sum over numbers multiple of a fixed integer which is not multiple of 3 and the Newman sum over numbers multiple of a fixed integer divisible by 3 is o(1) when the upper limit of summing tends to infinity. We also discuss a connection of our results with a digit conjecture on primes.
6
we have (27) Note that (28) √ x2 ) ≤ −1 ρ′ (x) = 2( 1 − x2 − √ 1 − x2 for x0 ≤ x ≤ 1, where 3 2 is the only positive root of the equation ρ(x) = x. Show that either x0 = = sin π 2m m 3 = gm < √ 3 2 √ tk = 2tk−1 1 − t2 k −1 = ρ(tk −1 ).
νr +1 −1 n=0 N1 − 1 n=N
e2πi(αn+ 2 s(n)) =
1
1
e2πi(αn+αN + 2 (s(N )+s(n))) =
νr +1 −1 n=0
= Fα (N ) + e Thus, by (17) and (18),
r
s(N )) 2πi(αN + 1 2
e2πi(αn+ 2 s(n)) .
λm < λ
(12)
9.10254164 . . . < µm ≤
9, 25251518 . . . , if (m, 3) = 1, 9.48358551 . . . , if (m, 3) = 3.
Below we prove the following results.
ESTIMATES OF NEWMAN SUM
Now distinguish two cases: 1) tk ≤ In case 1) tk = √
3 2
3 lπ rπ ⇆ = , (r, 3) = 1 2 m 3
1 + e2πi(α2
νh =ν0 ,ν1 ,...,νr k =1 r h
k −1 + 1 ) 2
k −1 + 1 ) 2


1 + e2πi(α2
h=0 k =1
.
= 2 sin(2k−1 απ )(sin(2k−1 απ ) − i cos(2k−1 απ ))
and, therefore, (22) 1 + e2πi(2
3
Theorem 1. If (m, 3) = 1 then (13) |Sm (x)| ≤ µm xλm .
Theorem 2. (Generalized Newman phenomena). If m > 3 is a multiple of 3 then (14) Sm (x) − 3 S3 (x) ≤ µm xλm . m
(8) where sin 2 (9) bm = sin sin (10) and thus, (11) and √
π m+1 m 3 π m ⌊ ⌋ m 3 π m m 3
µm =
4 , bm (2bm − 1) ln 2
Directly one can see that 3 > bm ≥ 2
ESTIMATES OF NEWMAN SUM
5
3. Proof of Theorem 1 Note that in (17) (20) By Lemma 1 we have
νh
r ≤ ν0 =
ln N . ln 2
|Fα (N )| ≤ (21) Furthermore, 1 + e2πi(2
k−1 α+ 1 ) 2
e2πiα2 +
j
(18)
+
0≤j1 <j2 ≤ν0 −1
e
2πiα(2j1 +2j2 )
−... =
ν 0 −1 k =0
(1 − e2πiα2 ),
k
ESTIMATES OF NEWMAN SUM
4
which corresponds to (17) for r = 0. Assuming that (17) is valid for every N with s(N ) = r + 1 let us consider N1 = 2νr a + 2νr+1 where a is odd, s(a) = r + 1 and νr+1 < νr . Let N = 2νr a = 2ν0 + . . . + 2νr ; N1 = 2ν0 + . . . + 2νr + 2νr+1 . Notice that for n ∈ [0, νr+1) we have s(N + n) = s(N ) + s(n). Therefore, Fα (N1 ) = Fα (N ) + = Fα (N ) +
Using Theorem 2 and (5) one can estimate x0 (m) in (6). E.g., one can prove that x0 (21) < e1207 . 2. Explicit formula for Sm (N ) We have Sm ( N ) =
N −1
1
Fα (N1 ) =
h=0
e
Pr
2πi(α
Ph−1
j =0
2νj + h ) 2
ν h −1 k =0
(1 + e2πi(α2
k+ 1 ) 2
k+ 1 ) 2
+
+e
2πi(α
j =0
) 2νj + r +1 2
νr +1 −1 k =0
1 + e2πi(α2
=
r +1
=
h=0
e
2πi(α
Ph−1
j =0
(29)
π m (30) tk ≤ sin m 3 or both tk > gm and tk tk+1 ≤ max (31) = sin sin
π m π m m 3 m 3
0≤l≤m−1
sin
lπ m

3 − sin
lπ m
=
√ 3 − sin √ 3 − sin
π m π m
m 3 m 3
, if m ≡ 1( mod 3) , if m ≡ 2( mod 3)
1
(16)
Fα (N ) =
e2πi(αn+ 2 s(n)) 0 ≤ α < 1.
Lemma 1. If N = 2ν0 + 2ν1 + . . . + 2νr , ν0 > νr > . . . > νr ≥ 0, then
r
(17)
Fα (N ) =
h=0 −1 j =0
e2πi(α = 0,
Ph−1
λ
3 65
λ

(4) and moreover,
xλ , x ≥ 2.
ESTIMATES OF NEWMAN SUM
2
(5)
2
x 6
λ
≤ S3 (x) ≤
55 x 3 65
λ
.
(m)
M.Drmota and M.Skalba [3] using a close function (Sm (x)) proved that if m is a multiple of 3 then for sufficiently large x, (6) Sm (x) > 0, x ≥ x0 (m).
n=0,m|n
(−1)
s(n)
1 = m
m−1 N −1 t=0 n=0
(−1)s(n) e2πi( m ) =
nt
(15)
1 = m
m−1 N −1 t=0 n=0
e2πi( m n+ 2 s(n)) .
t
1
Note that the interior sum has the form
N −1 n=0
k−1 α+ 1 ) 2
≤ 2 sin(2k−1απ ) .
According to (21) let us estimate the product
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