概率论与统计学原理chapt1english

Reliability可靠性
Since we use the information contained in the smaller sample to learn about the larger population and so we can not be certain that an inference about a population is correct. We need to know how good the inference is – its reliability (or risk), i.e. how to measure the uncertainty in inferences. DEF 1.8A measure of reliability is a statement (usually quantified) about the degree of uncertainty associated with a statistical inference. The measure of reliability shows the dialectical thinking. It also separates the science of statistics from the art of fortune-telling.
Types of Data
Data is a set of values (numbers, words, or symbols) collected for the variable from each of the units belonging to the sample or population. Two types of data: qualitative data quantitative data.
Fundamental elements of statistics
6. Parameter参数 is a numerical数值 参数 characteristic of an entire population. The “average” age of all MSNBC news viewers.
Qualitative data
DEF 1.10 Qualitative data are measurement that cannot be measured on a natural numerical scale; they can only be classified into one of a group of categories. For example, the response to the question ‘which subject is your first choice?’ is categorical. The choices are clearly ‘International Finance’, ‘Economics’, ‘Marketing’ …, or ‘Statistics’.
PROBABILITY & STATISTICS
Lecturer: Yu Yu Office: 8412 Email: yuyu@sandau.edu.cn
Course Outline
1. Descriptive Statistics: [Chapters 1 & 2] 2. Probability: [Chapters 3 – 5] 3. Inferential Statistics I: [Chapters 6 – 7]
Quantitative data
DEF 1.9 Quantitative data are measurements that are recorded on a naturally occurring numerical scale. The responses to questions such as “How old are you?” or "How tall are you?" are clearly numerical.
Survey
With a survey, the researchers sample a group of people, ask questions and record the responses. They collect information systematically and directly from respondents Survey methods: telephone surveys, mail surveys, internet survey, computer interviews, door-to-door personal interviews, and mall intercept studies.
1. Involves
Estimation Hypothesis Testing
Population?
2. Purpose
Make Decisions About Population Characteristics
Fundamental elements of statistics
1. Population总体 is a collection or set of units (usually 总体 people, objects, transactions, or events) that we are interested in studying. 2. An experimental unit试验单位 is an object (e.g., 试验单位 person, object, transaction, or event) upon which we collect data. 3. A variable变量 is a characteristic or property of 变量 interest about each individual population or sample unit.
Published sources
books, journals, news papers, internet, and so on. (Secondary data) Advantages and disadvantages of secondary data.
Designed Experiment
Course Grading
1. Regular Grade: 40%
Exercises: 10% Mid-term test: 20% Others: 10%
2. Final examination: 60%
Chapter 1
Statistics, Data, and Statistical Thinking
Learning Objectives
1. Define Statistics 2. Distinguish Descriptive & Inferential statistics 3. Define Population, Sample, Variable, Parameter, & Statistic 4. Distinguish Quantitative & Qualitative data 5. Four types of collecting data
Fundamental elements of statistics
7. Statistic统计量 is a numerical characteristic 统计量 of a sample. The “average” of 500 MSNBC news viewers. The value of a statistic can be calculated after a sample to be collected.
Example
According to USA Today, (Dec. 19, 1999), the average age of viewers of MSNBC cable television news programming is 50 years. Suppose a rival network executive hypothesizes that the average age of MSNBC viewers is less than 50. To test her hypothesis, she samples 500 MSNBC news viewers and collects the age of each. Describe the population. Describe the variable of interest. Describe the sample. Describe the inference推论.
Types of Statistical Applications
The field of statistics can be roughly subdivided into two areas: 1. descriptive statistics 描述型 2. inferential statistics 推论型
Collecting Data
Generally, we can obtain data in four different ways: 1. Data from a published source 2. Data from a designed experiment 3. Data from a survey 4. Data from an observational观察 study.
Fundamental elements of statistics
4. A sample样本 is a subset of the units of a 样本 population. 5. A statistical inference统计推断 is an estimate, 统计推断 testing, prediction, or same other generalization about a population based on information contained in a sample.
What is Statistics?
DEF 1.1 Statistics统计 is the science of data. This involves collecting, classifying, summarizing, organizing, analyzing, and interpreting numerical information.
A planned activity whose results yield a set of data. In a designed experiment, researchers control strictly over the units (people, objects, or things). This includes both the activities for selecting the units and obtaining the data values. Most of laboratory results are obtained in designed experiment.
Descriptive Statistics
1. Involves
Collecting Data Presenting Data Characterizing Data 50 25 0 Q1 Q2 Q3 Q4
$
2. Purpose
DescribBaidu Nhomakorabea Data
X = 30.5 S2 = 113
Inferential Statistics