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Sampling Methods

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1. Define the following terms in your own words.
• Population
• Sample
• Bias
• Design
• Response bias

2. Define and provide an example for each design method.
• Simple random sampling
• Systematic sampling
• Stratified sampling
• Cluster sampling

3. Choose one design method from the list above. Using your example, make a list of 2-3 advantages and 2-3 disadvantages for using the method.

4. The name of each student in a class is written on a separate card. The cards are placed in a bag. Three names are picked from the bag. Identify which type of sampling is used and why.

5. A phone company obtains an alphabetical list of names of homeowners in a city. They select every 25th person from the list until a sample of 100 is obtained. They then call these 100 people to advertise their services. Does this sampling plan result in a random sample? What type of sample is it? Explain.

6. The manager of a company wants to investigate job satisfaction among its employees. One morning after a meeting, she talks to all 25 employees who attended. Does this sampling plan result in a random sample? What type of sample is it? Explain.

7. An education expert is researching teaching methods and wishes to interview teachers from a particular school district. She randomly selects 10 schools from the district and interviews all of the teachers at the selected schools. Does this sampling plan result in a random sample? What type of sample is it? Explain.

8. Fifty-one sophomore, 42 junior, and 55 senior students are selected from classes with 516, 428, and 551 students respectively. Identify which type of sampling is used and explain your reasoning.

9. You want to investigate the workplace attitudes concerning new policies that were put into effect. You have funding and support to contact at most 100 people. Choose a design method and discuss the following:
a. Describe the sample design method you will use and why.
b. Specify the population and sample group. Will you include everyone who works for the company, certain departments, full or part-time employees, etc.?
c. Discuss the bias, on the part of both the researcher and participants.

10. A local newspaper wanted to gather information about house sales in the area. It distributed 25,000 electronic surveys to its readers asking questions about house sales in the past 6 months. Of the surveys sent out, 3.2% were returned. The results found that 92% of people did not sell their house in the past 6 months and 85% of people would expect a loss if they sold their house. The writer wants to use these results to conclude that the housing market is declining, and we are headed for a recession.
a. Explain the bias and sampling error in this study.
b. Should the writer conclude that the housing market is declining based upon this data?
c. Why or why not?

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SAMPLING
1. Define the following terms in your own words.
Answers
• Population
Population is the entire group about which information is needed.
• Sample
A sample is a smaller group of members of a population selected to represent the population.
• Bias
Bias is the difference between survey result and population value due to error in measurement, selection of non-representative sample or other factors.
• Design
The process of selecting sample elements from the sampling frame is called the sample design.
• Response bias
Response bias occurs when a participant provides a response that does not reflect their true thoughts, feelings, or behavior.
2. Define and provide an example for each design method.
Answers
• Simple random sampling
Simple random sampling is a method of probability sampling in which every unit has an equal nonzero chance of being selected.
Example
The name of each contestant is written on a separate card, the cards are placed in a bag, and three names are picked from the bag.
• Systematic sampling
Systematic sampling is a method of probability sampling in which the target population is arranged according to some ordering scheme and then selecting elements at regular intervals through that ordered list. That is, it involves a random start and then proceeds with the selection of every kth element from then onwards. In this case, k = (population size/sample size).
Example
Selecting every 49th student from a group of 496 students is systematic sampling.
• Stratified sampling
Stratified random sampling is a method of probability sampling in which the population is divided into different subgroups and samples are selected from each. In other words, we divide the target population into homogeneous subgroups or strata and draw random samples from each stratum and combine them into a single sample of the target population.
Example
49, 34, and 48 students are ...

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