Data Collection and Sampling Techniques

  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. Data Collection

 Telephone Surveys Benefits  Cheaper than personal interviews  More candid about opinions since there’s no face-to-face interactions 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

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

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

  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 Samples

  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 Random Sampling

  Researchers obtain systematic samples by numbering each subject of the population and then selecting every k th subject.  For example, suppose there were 1,000 people in a population and 50 were needed for the sample. 1000/50=20, so every 20 th 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 Systematic 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 Stratified 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. Cluster Sampling

  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. Convenience Sample

 1.In Woodbridge Township’s school district, all students from 3 schools are interviewed about their feelings on homework 2.Every 30 th light bulb on an assembly line is checked for deficiency 3.Restaurant managers are selected using random numbers to determine annual salaries 4.Customers entering Walmart are asked about how frequently they shop there Classify each sample as random, systematic, stratified, cluster, or convenience

 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 Classify each sample as random, systematic, stratified, cluster, or convienence

  Pg. 13 #1-7 Try it!