1. Section 2.1: Taking a Good Sample

2. Sampling Design  Design of a sample refers to the method used to collect the data.  A proper sampling design must start with a sample which is representative of the population.

3. Key Idea  If a sample is roughly representative of a population, you can estimate that the sample has roughly the same proportions as the population.  If we assume that PA is representative of the country, then if we know that 60% of people voted in the last presidential election and there are 12.4 million people in PA we can estimate the number of people in PA who voted.

4. To get reliable statistics, a sample must represent the population  Ex: In terms of households who watch tv, the USA is not representative of the world. In the USA approximately 98.5% of households have a tv but it’s about 13% worldwide.

5. Problems with Bad Sampling Designs  If your sample is created in such a way that it would tend to make it unrepresentative, then the sample is created using a biased method.

6. Examples of Poor Design Methods Nonresponse Poor wording of question/response bias Voluntary response: Call-in polls Convenience sampling Undercoverage

7. Need for Randomization  “Salty Soup” – Sampling from the top (or bottom) without first stirring gives a misleading point.  1970 Draft Lottery Example

8. How large of a random sample do you need for the sample to be reasonably representative of the population?  Most people think you need a large percentage of the population but in fact all that really matters is the number of people in the sample.  100 SU students represents the entire student body just as well as 100 voters represents the entire electorate of the USA.

9. Why? Back to the soup example  The soup tastes the same whether you use the same spoon in a large or small pot.  This idea determines the balance between how well the survey can measure the population and how much the survey costs.

10. How big of a sample do you need?  This depends on what you’re interested in estimating.  Soup example – Are you interested in just tasting the broth or more?  With a categorical variable, you’ll need at least enough subjects to see several respondents in each category.

11. What do pollsters do in practice?  Contact respondents by phone using computer generated random lists.  Pollsters list responses in random order to avoid biases.