Chapter 1.3

1. Chapter 1.3 Data Collection and Sampling Techniques

2. Data Collection • Data can be collected in a variety of ways. One of the most common methods is through the use of surveys. • The three most common methods of conducting a survey are the telephone survey, the mailed questionnaire, and the personal interview.

3. Telephone Surveys Benefits Disadvantages People who don’t have phones , don’t answer, or have blocked numbers (under coverage and non-response Tone of voice can influence response • Cheaper than personal interviews • More candid about opinions since there’s no face-to-face interactions

4. Mailed Surveys Benefits Disadvantages Low number of responses Inappropriate answers to questions Lack of understanding questions • Cover a wider geographic area • Less expensive • Respondents can remain anonymous

5. Personal Interview Benefits Disadvantages Most costly (training of interviewers) Interviewers may be biased • In-depth responses • Body language

6. Samples • Researchers use samples to collect data and information about a particular variable from a large population • Samples cannot be selected haphazardly because the information obtained may be biased • Unbiased samples give each subject in the population an equally likely chance of being selected • Statisticians use four basic methods of sampling: random, systematic, stratified, and cluster

7. Random Sampling • Random samples are selected by using chance methods or random numbers • Number each subject in the population and select as many as are needed for the sample. • Random number generators on computers or calculators are used to prevent bias

8. Systematic Sampling • Researchers obtain systematic samples by numbering each subject of the population and then selecting every kth subject. • For example, suppose there were 1,000 people in a population and 50 were needed for the sample. 1000/50=20 , so every 20th subject would be selected. • However, the first subject (numbered between 1 and 20) would be selected at random • Arrangement of subjects must be done carefully

9. Stratified Sampling • Researchers obtain stratified samples by dividing the population into groups (called strata) according to some characteristic important to the study, then sampling randomly from each group • For example, a high school might group students by grade and select a certain number of students from each grade

10. Cluster Sampling • In a cluster sample, the population is divided into groups, called clusters by some means. • The researcher randomly selects some of the clusters and uses all members of the cluster as subjects in the sample • For example, suppose that a researcher wants to conduct a study about apartment dwellers in a certain city. If there are 10 apartment buildings, 2 may be selected and all its residents interviewed.

11. Convenience Sample • In a convenience sample, researchers use subjects that are convenient • For example, a researcher interviews subjects entering a mall to determine the nature of their visit and which stores they will be patronizing.

12. Classify each sample as random, systematic, stratified, cluster, or convenience • In Woodbridge Township’s school district, all students from 3 schools are interviewed about their feelings on homework • Every 30th light bulb on an assembly line is checked for deficiency • Restaurant managers are selected using random numbers to determine annual salaries • Customers entering Walmart are asked about how frequently they shop there

13. Classify each sample as random, systematic, stratified, cluster, or convienence 5. A sample of 100 voters from a particular town are selected using random numbers 6. Job satisfaction by racial group is being surveyed at a particular company. Employees are grouped by race, then 5 subjects from each group are surveyed 7. A study on hospital patients in NYC is conducted by interviewing all patients at 3 hospitals

14. Try it! • Pg. 13 #1-7