Correlational research assesses relationships among naturally occurring variables with the goal of identifying predictive relationships.

The correlation coefficient is a quantitative index of the direction and magnitude of a predictive relationship.

Survey research is used to assess people's thoughts, opinions, and feelings.

Surveys can be specific and limited in scope or more global in their goals.

The best way to determine whether results of a survey are biased is to examine the survey procedures and analyses.

Survey research involves selecting a sample (or samples) and using a predetermined set of questions.

Careful selection of a survey sample allows researchers to generalize findings from the sample to the population.

Basic Terms of Sampling

The identification and selection of elements that will make up the sample is at the heart of all sampling techniques; the sample is chosen from the sampling frame, or list of all members of the population of interest.

Researchers are not interested simply in the responses of those surveyed; instead, they seek to describe the larger population from which the sample was drawn.

The ability to generalize from a sample to the population depends critically on the representativeness of the sample.

A biased sample is one in which the characteristics of the sample are systematically different from the characteristics of the population.

Selection bias occurs when the procedures used to select a sample result in the overrepresentation or underrepresentation of some segment(s) of the population.

Approaches to Sampling

Two approaches to selecting a survey sample are nonprobability sampling and probability sampling.

Nonprobability sampling (such as convenience sampling) does not guarantee that every element in the population has an equal chance of being included in the sample.

Probability sampling (simple random sampling and stratified random sampling) allows researchers to estimate the likelihood that their findings for the sample differ from those for the population.

In simple random sampling each element of the population has an equal chance of being included in the sample; in stratified random sampling, the population is divided into subpopulations (strata), and random samples are drawn from the strata.

Probability sampling is the method of choice for obtaining a representative sample.

Three methods for obtaining survey data are mail surveys, personal interviews, and telephone interviews.

Mail Surveys

Although mail surveys are quick and convenient, they may have the problem of responses bias when individuals fail to complete and return the survey.

Due to response bias, the final sample for a mail survey may not represent the population.

Personal Interviews

Although costly, personal interviews allow researchers to gain more control over how the survey is administered.

Interviewer bias occurs when survey responses are recorded inaccurately or when interviewers guide individuals' responses.

Telephone Interviews

Despite some disadvantages, telephone interviews have become the method of choice for completing brief surveys.

The three types of survey design are the cross-sectional design, successive independent samples design, and the longitudinal design.

Cross-Sectional Design

In the cross-sectional design one or more samples are drawn from the population(s) at one point in time.

Cross-sectional designs allow researchers to describe the characteristics of a population or the differences between two or more populations, and correlational findings from cross-sectional designs allow researchers to make predictions.

Successive Independent Samples Design

In the successive independent samples design, different samples of respondents from the population complete the survey over a time period.

The successive independent samples design allows researchers to study changes in a population over time.

The successive independent samples design does not allow researchers to infer how individual respondents have changed over time.

A problem with the successive independent samples design occurs when the samples drawn from the population are not comparable-that is, not equally representative of the population.

Longitudinal Design

In the longitudinal design, the same respondents are surveyed over time in order to examine changes in individual respondents.

Because of the correlational nature of survey data, it is difficult to identify the causes of individuals' changes over time.

As people drop out of the study over time (respondent mortality), the final sample may no longer be comparable to the original sample or represent the population.

Questionnaires as Instruments

Most survey research relies on the use of questionnaires to measure variables.

Demographic variables describe the characteristics of people who are surveyed.

The accuracy and precision of questionnaires requires expertise and care in their construction.

Self-report scales are used to assess people's preferences or attitudes.

Reliability and Validity of Self-Report Measures

Reliability refers to the consistency of measurement, and is frequently assessed using the test- retest reliability method.

Reliability is increased by including many similar items on a measure, by testing a diverse sample of individuals, and by using uniform testing procedures.

Validity refers to the truthfulness of a measure: Does it measure what it intends to measure?

Construct validity represents the extent to which a measure assesses the theoretical construct it is designed to assess; construct validity is determined by assessing convergent validity and discriminant validity.

Constructing a Questionnaire

Constructing a questionnaire involves deciding what information should be sought and the type of questionnaire, writing a draft of the questionnaire, pretesting the questionnaire, and concluding with specifying the procedures for its use.

The wording of questionnaires should be clear and specific using simple, direct, and familiar vocabulary.

The order in which questions are asked on a questionnaire must be considered seriously because the order can affect respondents' answers.

Correspondence Between Reported and Actual Behavior

Survey research involves reactive measurement because individuals are aware that their responses are being recorded.

Social desirability refers to pressures respondents sometimes feel to respond as they "should" believe rather than how they actually believe.

Researchers can assess the accuracy of survey responses by comparing these results with archival data or behavioral observations.

Correlation and Causality

When two variables are related (correlated), we can make predictions for the variables; however, we cannot make inferences about the causes of the relationship.

When a relationship between two variables can be explained by a third variable, the relationship is said to be "spurious."

Correlational evidence, in combination with a multimethod approach, can help researchers identify potential causes of behavior.