1. Jada Hardy & Malakai Miller
Chapter 12
Jada Hardy & Malakai Miller

2. 1. Examine Part of the Whole
Population: A group of individuals
Sample: Smaller group of individuals selected from the population
Sample Surveys: surveys designed to ask questions of a small group of people in the hope of learning something about the entire population
Biased: Bias is systematic favoritism that is present in the data collection process, resulting in lopsided, misleading results.

3. Sample v. Population

4. Bias
Sampling methods that, by their nature, tend to over- or under- emphasize some characteristics of the population.
There is usually no way to fix a biased sample and no way to salvage useful information from it.
The best way to avoid bias is to select individuals for the sample at random

5. 2. Randomizing Randomizing: Selecting people at random.
It protects us from the influences of all the features of our population, even ones that we may not have thought about.
It does that by making sure that on average the sample looks like the rest of the population.
Randomizing protects us from bias, it actually makes it possible for us to draw assumptions about the population when we see only a sample

6. 3. It’s the Sample Size

7. Does a Census Make Sense?
Census: Sampling the entire population is a census.
There are problems with taking a census:
It can be difficult to complete a census—there always seem to be some individuals who are hard to locate or hard to measure ; or it may be impractical- food.
Populations rarely stand still. Even if you could take a census, the population changes, so it’s never possible to get a perfect measure.

8. Populations & Parameters

9. Simple Random Samples
Representative: A sample that reflects the corresponding parameters accurately.
Simple Random Sample: A method where each combination of people has an equal chance of being selected.
Sampling frame: A list of individuals from which the sample is drawn.

10. Notation

11. Simple Random Samples
Simple Random Sample (SRS)– Each person and combination of people have an equally likely chance of being selected.

12. Stratified Random Sampling

13. Cluster Sampling

14. Multistage Samples

15. Systematic Sampling

16. Convenience Sample
Examples:

17. Who’s

18. Things to remember…

19. What Else Can Go Wrong? Work hard to avoid influencing responses.
Response bias refers to anything in the survey design that influences the responses.
For example, the wording of a question can influence the responses

20. Here’s a Video