1. Chapter 12 Sample Surveys
Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley

2. A subset of the population.
The collection of all outcomes, responses, measurements, or counts that are of interest.
Sample
A subset of the population.
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3. Example: Identifying Data
Ex: In a recent survey, 1500 adults in the United States were asked if they thought there was solid evidence for global warming. Eight hundred fifty-five of the adults said yes. Identify the population and the sample. Describe the data set. (Adapted from: Pew Research Center)
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4. Sample size- is the number of individuals in a sample size
Sample size- is the number of individuals in a sample size. We use n to represent the sample size.
Sampling Frame-a list of individuals from whom the sample is drawn.

5. Parameter and Statistic
A number that describes a population characteristic.
Average age of all people in the United States
Statistic
A number that describes a sample characteristic.
Average age of people from a sample of three states
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6. Example: Distinguish Parameter and Statistic
Decide whether the numerical value describes a population parameter or a sample statistic.
A recent survey of a sample of college career centers reported that the average starting salary for petroleum engineering majors is $83,121. (Source: National Association of Colleges and Employers)
Solution:
Sample statistic (the average of $83,121 is based on a subset of the population)
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7. Example: Distinguish Parameter and Statistic
Decide whether the numerical value describes a population parameter or a sample statistic.
The 2182 students who accepted admission offers to Northwestern University in 2009 have an average SAT score of (Source: Northwestern University)
Solution:
Population parameter (the SAT score of 1442 is based on all the students who accepted admission offers in 2009)
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8. Sampling Techniques Simple Random Sample
Every possible sample of the same size has the same chance of being selected.
Example:
General Motors wants to administer a satisfaction survey to its current customers. Using their customer database, the company randomly select 80 customers and asks about their level of satisfaction with the company.
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9. A sample that consist of the entire population is called a census.
EX: The average weight of 25 students in math classes.

10. Other Sampling Techniques
Stratified Sample
Divide a population into groups (strata) and select a random sample from each group.
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11. Other Sampling Techniques
Cluster Sample
Divide the population into groups (clusters) and select all of the members in one or more, but not all, of the clusters.
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12. Other Sampling Techniques
Systematic Sample
Choose a starting value at random. Then choose every kth member of the population.
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13. A convenience sample consist of the individuals who are conveniently available.
EX: A radio station asks its listeners to call in their opinion regarding the use of pesticides in residential areas.

14. Sample schemes that combine several sampling method are called multistage samples.

15. Bias
A statistic is biased if it is calculated in such a way that is systematically different from the population parameter of interest.
The best defense against bias is Randomization, in which each individual is given a fair, random chance of selection.

16. Voluntary response bias- Bias introduced to a sample when individuals can choose on their own whether to participate in the sample.
Nonresponse bias-Bias introduced to a sample when a large fraction of those sample failed to respond.
Anything in a survey design that influences responses falls under the heading of response bias.
Undercoverage bias, in which some portion of the population is not sampled at all or has a smaller representation in the sample than it has in the population.

17. :
undercoverage, in which some portion of the population is not sampled at all or has a smaller representation in the sample than it has in the population.

18. In a voluntary response sample, a large group of individuals is invited to respond, and all who do respond are counted.
Voluntary response samples are almost always biased, and so conclusions drawn from them are almost always wrong.

19. Notation
We typically use Greek letters to denote parameters and Latin letters to denote statistics.