1. Agresti/Franklin Statistics, 1 of 33 Chapter 1 Statistics: The Art and Science of Learning from Data Learn …. What Statistics Is Why Statistics Is Important

2. Agresti/Franklin Statistics, 2 of 33  Chapter 1 Learn… How Data is Collected How Data is Used to Make Predictions

3. Agresti/Franklin Statistics, 3 of 33  Section 1.1 How Can You Investigate using Data?

4. Agresti/Franklin Statistics, 4 of 33 Health Study Does a low-carbohydrate diet result in significant weight loss?

5. Agresti/Franklin Statistics, 5 of 33 Market Analysis Are people more likely to stop at a Starbucks if they’ve seen a recent TV advertisement for their coffee?

6. Agresti/Franklin Statistics, 6 of 33 Heart Health Does regular aspirin intake reduce deaths from heart attacks?

7. Agresti/Franklin Statistics, 7 of 33 Cancer Research Are smokers more likely than non- smokers to develop lung cancer?

8. Agresti/Franklin Statistics, 8 of 33 To search for answers to these questions, we… Design experiments Conduct surveys Gather data

9. Agresti/Franklin Statistics, 9 of 33 Statistics is the art and science of: Designing studies Analyzing data Translating data into knowledge and understanding of the world

10. Agresti/Franklin Statistics, 10 of 33 Example from the National Opinion Center at the University of Chicago: General Social Survey (GSS) provides data about the American public Survey of about 2000 adult Americans

11. Agresti/Franklin Statistics, 11 of 33 Example from GSS: Do you believe in life after death?

12. Agresti/Franklin Statistics, 12 of 33 Three Main Aspects of Statistics Design Description Inference

13. Agresti/Franklin Statistics, 13 of 33 Design How to conduct the experiment How to select the people for the survey

14. Agresti/Franklin Statistics, 14 of 33 Description Summarize the raw data Present the data in a useful format

15. Agresti/Franklin Statistics, 15 of 33 Inference Make decisions or predictions based on the data.

16. Agresti/Franklin Statistics, 16 of 33 Example from GSS: On a typical day, about how many hours do you personally watch television?

17. Agresti/Franklin Statistics, 17 of 33 What percentage of the people surveyed reported watching 0 hours of TV a day?

18. Agresti/Franklin Statistics, 18 of 33 Example: Harvard Medical School study of Aspirin and Heart attacks Study participants were divided into two groups Group 1: assigned to take aspirin Group 2: assigned to take a placebo

19. Agresti/Franklin Statistics, 19 of 33 Example: Harvard Medical School study of Aspirin and Heart attacks Results: the percentage of each group that had heart attacks during the study: 0.9% for those taking aspirin 1.7% for those taking placebo

20. Agresti/Franklin Statistics, 20 of 33 Example: Harvard Medical School study of Aspirin and Heart attacks Can you conclude that it is beneficial for people to take aspiring regularly? Example: Harvard Medical School study of Aspirin and Heart attacks

21. Agresti/Franklin Statistics, 21 of 33  Section 1.2 We Learn About Populations Using Samples

22. Agresti/Franklin Statistics, 22 of 33 Subjects The entities that we measure in a study Subjects could be individuals, schools, countries, days,…

23. Agresti/Franklin Statistics, 23 of 33 Population and Sample Population: All subjects of interest Sample: Subset of the population for whom we have data

24. Agresti/Franklin Statistics, 24 of 33 Example Format Picture the Scenario Question to Explore Think it Through Insight Practice the concept

25. Agresti/Franklin Statistics, 25 of 33 Example: The Sample and the Population for an Exit Poll In California in 2003, a special election was held to consider whether Governor Gray Davis should be recalled from office. An exit poll sampled 3160 of the 8 million people who voted.

26. Agresti/Franklin Statistics, 26 of 33 What’s the sample and the population for this exit poll? The population was the 8 million people who voted in the election. The sample was the 3160 voters who were interviewed in the exit poll. Example: The Sample and the Population for an Exit Poll

27. Agresti/Franklin Statistics, 27 of 33 Descriptive Statistics Methods for summarizing data Summaries usually consist of graphs and numerical summaries of the data

28. Agresti/Franklin Statistics, 28 of 33 Types of U.S. Households

29. Agresti/Franklin Statistics, 29 of 33 Inference Methods of making decisions or predictions about a populations based on sample information.

30. Agresti/Franklin Statistics, 30 of 33 Parameter and Statistic A parameter is a numerical summary of the population A statistic is a numerical summary of a sample taken from the population

31. Agresti/Franklin Statistics, 31 of 33 Randomness Simple Random Sampling: each subject in the population has the same chance of being included in that sample Randomness is crucial to experimentation

32. Agresti/Franklin Statistics, 32 of 33 Variability Measurements vary from person to person Measurements vary from sample to sample

33. Agresti/Franklin Statistics, 33 of 33 a. To describe whether a sample has more females or males. b. To reduce a data file to easily understood summaries. c. To make predictions about populations using sample data. d. To predict the sample data we will get when we know the population. Inferential Statistics are used: