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

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

Overview of Sections 3.1- 3.3 Where to find data?

NCES Webpage – An Example of Available Data

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

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.

Design of Experiments – Basic Principles

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

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

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 -

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 ????

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)!!!

Example 3.26 (page 233) Supposes the population parameter is p = 0.60 The sampling distribution for when n = 2500. Compare (shape, center, spread) to the previous sampling distribution when n = 100.

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 ?

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!

Problem 3.66 Page 241