1. 1 AM310 Introductory Statistics Instructor: Haitao Yin

2. 2 Agenda for Today Introductions Structure of the course  Syllabus review and questions  Course expectations and requirements  Orientation to web site Basic concepts

3. 3 Textbook 机械工业出版社 当当价：￥ 92.80 Public health application

4. 4 Grading policy 10%Attendance and Participation 20%Four Assignments 20%Midterm 50%Final Exam (Comprehensive)

5. 5 Course Website http://cc.sjtu.edu.cncc.sjtu.edu Search for 应用统计学 Click on 主讲教师

6. 6 Questions?

7. 7 Topics covered today 1.What is statistics? 2.Data 3.Descriptive and Inferential Statistics

8. 8 What is Statistics? http://www.who.int/en/ Statistics is the art and science of collecting, analyzing, presenting, and interpreting data. Purpose of Statistics: Reveal information in the most straightforward manner.

9. 9 Data Elements Variables Observations Measures

10. 10 Types of Measurement

11. 11 Types of data qualitative data (a.k.a. attribute data, categorical data): values are based upon assignment to defined groups quantitative data: values take on numeric values based upon degree or extent of the property that exists  discrete quantitative data: values are integers or whole numbers  continuous quantitative data: values may take on any value over the entire range of values

12. 12 Types of data Cross-sectional Time Series

13. 13 Two Type of Statistics Descriptive statistics:  the collection, presentation, and description of numerical data Inferential statistics:  interpreting the values resulting from descriptive statistics and then using them to make decisions

14. 14 Examples of Descriptive Statistics Health Expenditure Frequency Percent Frequency Large545 Medium327 Small327 Totals11100

15. 15 Examples of Descriptive Statistics

16. 16 Inferential statistics population: the set of all elements of interest in a particular study sample: a subset of the population chosen for study

17. 17 Before probability theory … Population and Sample  It is very important for the remainder of the course to be able to differentiate between a population of interest and a sample that gives information about a population.

18. 18 Population, Sample The population in a statistical study is the entire group of individuals about which we want information. A sample is a part of the population from which we actually collect information, used to draw conclusions about the whole.

19. 19 Example Each week, the Gallup Poll questions a sample of about 1500 adult U.S. residents to determine national opinion on a wide variety of issues, such as the approval rating of the president.  What is the population of interest?  What is the sample?

20. 20 Example Each week, the Gallup Poll questions a sample of about 1500 adult U.S. residents to determine national opinion on a wide variety of issues, such as the approval rating of the president.  What is the population of interest? Population: All U.S. adults  What is the sample? Sample: 1500 sampled U.S. adults

21. 21 Statistical Inference Infer conclusions about the wider population from data on selected individuals (sample) To think about inference, we must keep straight whether a number describes a sample or a population

22. 22 Keep In Mind the Big Picture Sample (Population) Parameter (Sample) Statistic Statistical Inference Population

23. 23 Basic terms in data collection census: a list of all the elements belonging to a population sampling frame: a list of elements belonging to the population from which the sample will be drawn (should be representative of the population)  Example: Using a telephone directory to represent all households with listed telephone numbers. sample design: procedures used to collect sample data

24. 24 Take Away What are we going to study in this semester? Think about ……  How are you going to study statistics?  How are you going to spend your four years?