new version of spss

1．One way ANOV APurpose:One way ANOV A is used to compare means of highest year of school completed for respondents who are very happy, pretty happy and not too happyMeasurement of variables:Highest year of school completed (continuous variable)General happiness (categorical variable)1.Assumption:Outcome: Nearly normal2.Homogeity of variance test:Outcome: Pvalue=9.8%>5% 3.One way ANOV A:Outcome: Pvalue=0.000<0.1%4.Post HOC test: equal variance assumed ( Bonfeeron )CONCLUSION:Pvalue=0.00<0.1%. Results are significant at 0.1% level. People who are very happy have significantly higher school completed (mean value=13.34) compared to people who are pretty happy (mean value=12.78) and compared to people who are not too happy (mean value=12.88). So the more years of education finished, the happier people feel.2. Multi-regressionsPurpose:Multiple regression analyses the influence of father’s education, mother’s education, race and professions on number of brothers and sistersMeasurement:Number of brothers and sisters (continuous variable)Mother’s highest year of school completed (continuous variable) Father’s highest year of school completed (continuous variable) Race1 [1white 2 black] (categorical variable)Profession [1officer 2farmer 3worker] (categorical variable)Recode “profession” (1officer 2farmer 3worker) into “farmer” and “worker”[dummy variables]Recode “race1” (1white 2black) into “race2” (1 white 0black)[dummy variable]Coefficients aIndependent variableDependent variableCONCLUSIONF test of 22.945(Sig=0.000) shows that the overall regression is significant. R2 of 0.106 shows that 1.06% of the variation in number of brothers and sisters is explained by the regression. But the fit of the regression is weak.P values of the independent variables are significant at the 5% level, but the coefficient show that both of the father’s and mother’s highest year school completed have a negative significant influence on the number of brothers and sisters.T value of -4.068(sig=0.00) shows that race influences number of brothers and sisters at the 0.1% level. Coefficient of -1.377 show that the number of brothers and sisters of the white is less than the black. Respondents who are workers and farmers have more children, compared with those who are officers. In conclusion, people whose profession is low have more children.3.F r e q u e n c y D i s t r i b u t i o nPurpose:Frequency displays values (numbers and percentage) for the three categories (too low, about right and too high) of residents’ federal income taxMeasurement:Residents’ federal income tax (categorical variable)Residents’ Federal Income TaxFrequency Percent Valid Percent Cumulative PercentValid Too High 541 35.7 58.0 58.0 About Right 380 25.0 40.8 98.8 Too Low 11 .7 1.2 100.0 Total 932 61.4 100.0Missing NAP 524 34.5 DK 46 3.0 NA 15 1.0 Total 585 38.6Total 1517 100.0CONCLUSION58% of the Resident's Federal Income Tax is too high, only 1.2% of the Resident's Federal Income Tax is low. Overall the majority of the Resident's Federal income tax is high.4. INDEPENDENT SAMPLE T-TEST Purpose:Independent sample t test is used to test whether the mean scores of highest year of school completed is significantly different for “active part in world’s affairs” and “stay out of the world’s affairs”.Measurement:Highest year of school completed (continuous variable)Take active part in world’s affairs (categorical variable)AssumptionOutcome: the distribution is almost normalCONCLUSIONP value=0.000<0.1%. Results are significant at the 0.1% level. People who have higher education are significantly active part in the world’s affair (mean value=13.21), compared with those who stay out of the world’s affair (mean value=11.87). However, this difference is not much which shows the highest year of school completed doesn’t really have influence on respondents’ attitude towards the world’s affair.5. Chi-squarePurpose:This test assesses whether there is an association between “To work hard” and “general happiness”Measurement:To work hard (categorical variable)General happiness (categorical variable)Output:Association between “To Work Hard” and “General Happiness” Cross tabulationGeneral Happiness TotalHappy Not veryhappyTo Work Hard Most ImportantCount 127 19 146% within To WorkHard87.0% 13.0% 100.0% 2nd ImportantCount 316 37 353% within To WorkHard89.5% 10.5% 100.0% 3rd ImportantCount 282 36 318% within To WorkHard88.7% 11.3% 100.0% 4th ImportantCount 132 11 143% within To WorkHard92.3% 7.7% 100.0% Least ImportantCount 9 6 15% within To WorkHard60.0% 40.0% 100.0%Total Count 866 109 975 % within To WorkHard88.8% 11.2% 100.0%CONCLUSIONSig=0.005<1%.Results are significant at the 1% level. So to work hard and general happiness are significantly related. People who think work is 4th important (92.3%) and people who think work is 2nd important (89.5%) are more likely to find life is happy than people who think work is the least important (60%). Quite a high proportion of people who think work are not very important or the least important find life is not very happy (40%).6.One simple T-testPurpose:The one sample t test is used to compare the mean of highest year of school completed with 12 years’ education (12-year education is the American elemental education stage. If more than 12, that can be regarded as higher education stage)Measurement:Highest year of school completed (continuous variable)12(ratio)From the histogram, it shows that the distribution is nearly normal.One-Sample StatisticsN Mean Std.Deviation Std. Error MeanHighest Year ofSchool Completed1510 12.88 2.984 .077CONCLUSIONP value=0.000<0.1%. Results are significant at the 0.1% level. Mean highest year of school completed is significantly different from 12 years (Mean=12.88). It’s more than 12 years.7. Cross tabulationPurpose:Test whether there is a relationship between “happiness level” and “education level”. Measurement:Happiness level (categorical variable)Education level (categorical variable)CONCLUSIONThe results seem to indicate that the higher education, the more happy people feel. For example, 90% of the respondents whose education level is between 11 and 20 years feel happy. Only 10% are not happy.8. Paired sample t-test Purpose:To test the difference of scores between preparation and without preparation. Measurement:Scores after preparation: before the test, you make full preparation (continuous variable) Scores without preparation: before the test, you don’t prepare (continuous variable)Assumption: scores after preparation - scores without preparationThe distribution is nearly normalPaired Samples StatisticsMean N Std.Deviation Std. Error MeanPair 1 scores afterpreparation88.30 1517 12.163 .312 scores withoutpreparation50.18 1517 13.700 .352CONCLUSIONPvalue=0.000< 0.1%. Results are significant at the 0.1% level. The scores have significantly increased by more than 38 points after preparation.。