1. David S. Moore • George P. McCabe Practice of Statistics
Introduction to the
Practice of Statistics
Fifth Edition
Chapter 3:
Producing Data
Copyright © 2005 by W. H. Freeman and Company

2. Chapter 3 – Producing Data
3.1 First Steps
3.2 Design of Experiments
3.3 Sampling Design
3.4 Toward Statistical Inference

3. Overview of Sections
Where to find data?

4. NCES Webpage – An Example of Available Data

5. Producing Data
Statistical designs for producing data rely on either sampling or experiments.

6. Design of Experiments - Terminology
Factors – Explanatory variables in an experiment.
Control Group – Used to control lurking variables (such as response to a placebo).
Uncontrolled studies in medicine biased in favor of finding treatment effective.

7. Design of Experiments – Basic Principles

8. Randomized Comparative Experiment
Completely Randomized Design Comparing 6 Treatments
Block Design with 3 Treatments

9. Sampling Design Basics
ratemyprofessor.com
Label all individuals in population - use software to get random sample.

10. Section 3.4 – Toward Statistical Inference
Parameter
Statistic
Average Height of all American Women -
Average Height of a SRS of 97 American Women -
True Percent (or Proportion) of Americans that Approve of Job GW is Doing as President - p
Percent (or proportion) of a SRS of 114 Americans that Approve of Job GW is Doing as President -

11. Will each of us have the same value of the statistic ????
Example 3.25 (page 233)
Suppose we want to estimate the percent of all adult US residents that find clothes shopping time-consuming and frustrating. This fixed (but unknown) population proportion is a parameter and we will give it the symbol p.
Suppose we each take a SRS of 20 adults and compute the proportion of those adults that find clothes shopping time-consuming and frustrating. This proportion is a statistic and we will give it the symbol
Will each of us have the same value of the statistic ????

12. Example 3.26 (page 233)
Supposes the population parameter is p = 0.60
The statistic will vary from sample to sample (given a fixed sample size)!!!

13. Example 3.26 (page 233)
Supposes the population parameter is p = 0.60
The sampling distribution for when n = Compare (shape, center, spread) to the previous sampling distribution when n = 100.

14. Sampling Distribution Terminology and Concepts
What can we say about the bias of our two previous sampling distributions (does appear unbiased)?
What can we say about the variability of the statistic based on our two previous sampling distributions for ?

16. Managing Bias and Variability of Statistics
Assuming a SRS from a “large” population, it is the sample size that affects the variability of the statistic, not the population size!

17. Problem 3.66
Page 241