1. The Language of Sampling
Lecture 5
Sections 2.1 – 2.4
Fri, Sep 3, 2004

2. Why Sample?
Why?

3. The Language of Sampling
Unit or subject– An individual member of the population.
Variable – The characteristic of interest to be measured for each unit in the sample.
Population size – The number of members in the population, denoted by N.
Sample size – The number of members in the sample, denoted by n.

4. Parameters and Statistics
Parameter – A numerical characteristic of the population. Its value depends on the entire population.
Statistic – A numerical characteristic of a sample. Its value depends on the sample.

5. Random vs. Representative
Random sample – The members of the sample are selected at random from the population; each member has the same chance to be selected.
Representative sample – In all of its characteristics, the sample resembles the population.

6. Examples Example 2.2, p. 78 – Defective Parts.
Example 2.3, p. 78 – Parameter or Statistic?
Let’s Do It! 2.1, p. 78 – Parameter or Statistic?

7. Bias
A sampling method is biased if it produces results that systematically differ from the truth about the population.

8. Example
Example 2.5, p. 79 – Biased Too High?

9. Some Biased Sampling Methods
Convenience sampling – Sampling only those units that are easily accessible.
Volunteer sampling – Sampling only those units that volunteer to be sampled.

10. Three Types of Bias
Selection bias – The systematic tendency to include or to exclude a certain kind of unit.
Nonresponse bias – Bias resulting from some selected units not responding.
Response bias – Bias arising from the subject trying to meet the interviewer’s perceived expectations.

11. Example Example 2.9, p. 81 – Phone Surveys.
Example 2.13, p. 82 – Prison Sentences.

12. Let’s Do It! Let’s do it! 2.2 – Is It Biased?
Let’s do it! 2.3 – Family Size.