Chapter 1.3

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 SurveysBenefits

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 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

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 30th 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!