Correlational Research Assess relationships among naturally occurring variables Attitudes, preferences, intelligence, personality traits, feelings, age, sex Use correlation coefficients to describe a relationship between two variables determine a predictive relationship between two variables Researchers are not interested simply in the responses of those surveyed inference: use a sample to describe the larger population careful selection of a survey sample generalize the findings from the sample to the population

Sex, Romance, and Relationships a survey about sexual attitudes and practices

Correlations: Measuring and Describing Relationships A correlation is a statistical method used to measure and describe the relationship between two variables. A relationship exists when changes in one variable tend to be accompanied by consistent and predictable changes in the other variable. A correlation typically evaluates three aspects of the relationship: the direction the form the strength

Best Fit Line Figure 15-1 (p. 510) The relationship between exam grade and time needed to complete the exam. Notice the general trend in these data: Students who finish the exam early tend to have better grades.

Scatter Plot of Family Income and Student’s average grade Figure 15.2 page 511 Correlation data showing the relationship between family income (X) and student grades (Y) for a sample of n=14 high school students. The scores are listed in order from lowest to highest family income and are shown in a scatter plot.

Correlations: Measuring and Describing Relationships The direction of the relationship is measured by the sign of the correlation (+ or -). A positive correlation means that the two variables tend to change in the same direction; as one increases, the other also tends to increase. A negative correlation means that the two variables tend to change in opposite directions; as one increases, the other tends to decrease.

Figure 15-3 (p. 512) Examples of positive and negative relationships Figure 15-3 (p. 512) Examples of positive and negative relationships. (a) Beer sales are positively related to temperature. (b) Coffee sales are negatively related to temperature.

Correlations: Measuring and Describing Relationships The strength or consistency of the relationship is measured by the numerical value of the correlation. Value of r can range from 0 to 1. A value of 1.00 indicates a perfect relationship A value of zero indicates no relationship r value does not have a linear relationship with strength of the correlation. Use coefficient of determination ( r2 ) which measures the proportion of variability instead of r so if r = 0.80 then r2 = 0.64 which is a better indicator of strength

Figure 15-4 (p. 513) Examples of different values for linear correlations: (a) shows a strong positive relationship, approximately +0.90; (b) shows a relatively weak negative correlation, approximately –0.40; (c) shows a perfect negative correlation, –1.00; (d) shows no linear trend, 0.00.

Correlations: Measuring and Describing Relationships To compute a correlation you need two scores, X and Y, for each individual in the sample. The Pearson correlation requires that the scores be numerical values from an interval or ratio scale of measurement. Other correlational methods exist for other scales of measurement.

Survey Research Widely used by Social, Political and Psychological scientists Surveys are used to describe people’s opinions, attitudes, and preferences make predictions about people’s behavior Scope of surveys specific and limited - views about a specific TV program global in their goals - about TV habits in general Bias in surveys determine by examining procedures and analyses not just because it is sponsored by an organization with a vested interest Typical survey research a sample of people completes a questionnaire using a predetermined set of questions

Basic Terms of Sampling Population: set of all cases of interest. For example: current students at your institution current residents of your city citizens of the United States Everyone on the planet Sampling Frame: list of the members of a population. For example, registrar’s list of all currently registered students Frame should reflect the population May be difficult to get an adequate frame Sample: subset of the population drawn from the frame Students in your class as a sample of current students at your institution (or your city, United States, the planet) Element: each member of the population.

Figure 5.1 Illustration of relationship among four basic terms in sampling

Goal: Sample should represent the population. Obtaining a Sample Goal: Sample should represent the population. Characteristics of participants in the sample should be similar to those of the entire population. Example: Which sample represents a population that is 30% freshman, 30% sophomore, 20% junior, 20% senior? Sample A Sample B 30 freshmen, 30 sophomores, 60 freshmen, 60 sophomores, 20 juniors, 20 seniors 40 juniors, 40 seniors Both! But note: The samples are representative on one feature only!

Obtaining a Sample A biased sample occurs when the characteristics of the sample differ systematically from those of the target population. under-represent a segment of the population Population is 65% female Sample is 50% female over-represent a segment of the population. Population is 35% male Sample is 50 % male For example, most samples in psychology research overrepresent college students underrepresent individuals who are not in college. Most research underrepresents individuals from diverse cultures

Two sources of biased samples: Obtaining a Sample Two sources of biased samples: Selection bias occurs when the researcher’s procedures for selecting a sample result in one or more segments of the population being under- or over-represented. Example: Researcher places sign-up sheets for a research study in a Psychology Department. Psychology students are likely to be over-represented because of the selection procedure. Response bias occurs when individuals selected for the initial sample do not complete and return the survey. Example: People who receive the survey aren’t interested, they’re worried about privacy, have vision or other problems, don’t have time, etc. Final sample will only represent the population of people who are interested, not worried, have good vision, time, etc.

Examples of response bias Survey of sexual attitudes for example, should sex be more openly discussed in schools? Whom is most likely to return survey? Whom is most likely to not return the survey?

Approaches to Sampling Sampling refers to the procedures used to obtain a sample. Two basic approaches to sampling are Nonprobability sampling Probability sampling

Approaches to Sampling Nonprobability sampling: No guarantee that each member of the population has an equal chance of being included in the sample. “Convenience sampling” occurs when the researcher selects individuals who are available and willing to respond to the survey. Magazine surveys, Internet surveys, Call-In surveys Can have very large sample size Students in a classroom Lots of psychological research uses convenience samples but this can be OK How do you know if the sample is representative?

Approaches to Sampling Probability sampling: All members of a population have an equal chance of being selected for the survey Simple random sample Random selection from a sampling frame (list) of people in the population Effective Sample size is related to variability of the population Stratified random sample Divide population into strata and sample proportionally Random samples are then drawn from the strata. For example, strata from a university population potentially include freshmen, sophomores, juniors, seniors Stratified random sampling increases the likelihood that the sample will represent the population.

Four methods for obtaining survey data are: Survey Methods Four methods for obtaining survey data are: mail surveys, personal interviews, telephone interviews, and Internet surveys. Each method has advantages and disadvantages. Choose depending method based on research question.

Survey Methods Mail surveys quick and convenient, self-administered, best for highly personal or embarrassing topics. may have the problem of response bias when people selected for the survey sample don’t complete and return their survey. Due to response bias, the final sample may not be representative of the population. Because mailed surveys are self-administered respondents are free to interpret questions as they see fit leading to possible differences in how people respond to questions. Questions must be self explanatory

Survey Methods (continued) Personal Interviews are costly, but researchers gain more control over how the survey is administered, and how people interpret survey questions. Interviewers can seek clarification of answers. potential problem: interviewer bias. Interviewer bias occurs when interviewer records only selected portions of respondents’ answers, or interviewer words questions differently to fit particular respondents. Interviewers must be highly motivated, carefully trained, and supervised.

Survey Methods (continued) Telephone Interviews brief surveys can be completed efficiently and with greater access to the population. Random-digit dialing technology allows researchers to select random samples. Interviewers can be supervised easily from one location Potential problems include selection bias because only people with phones can be included response bias in that people may refuse solicitations to complete surveys over the phone interviewer bias

Survey Methods (continued) Internet Surveys The Internet allows for efficient, low-cost means to survey very large samples. Samples can be very diverse and access typically underrepresented samples. Potential problems include selection bias because access to computers and Internet required response bias lack of control over the research environment

Survey Methods Ways to increase survey response rate (and lessen problems associated with response bias): Questionnaire has a “personal touch” (e.g., respondent are addressed by name and not simply “Dear student”) Responding requires a minimum of effort Topic of survey is intrinsically interesting to respondent Respondent identifies with the organization or researcher who is sponsoring the survey.

Survey Research Designs A research design is a plan for conducting a research project. There are three types of survey research designs: Cross-sectional design Successive independent samples design Longitudinal design The survey design researchers choose depends on their research question.

Survey Research Designs Cross-sectional Survey Design A sample is selected from one or more populations at one time point. The responses are used to describe and make predictions for the population at that point in time. If two or more samples are drawn from different populations, the populations can be compared. Researchers cannot assess changes over time with cross-sectional designs.

Survey Research Designs Successive Independent Samples Design A series of cross-sectional surveys over time. A different sample of people completes the survey each time. Each sample is selected from the same population. Responses from the sample are used to describe the population at each point in time. Researchers can compare the survey responses from each sample to see how the population changes over time. Successive independent samples designs don’t tell us whether individuals change over time (because different individuals complete the survey each time). Problem of noncomparable samples: If different populations are sampled at each time, we don’t know if responses differ because of true changes over time, or because different populations were sampled.

Survey Research Designs Longitudinal Research Designs The same sample of individuals completes the survey at different points in time. This allows researchers to assess how individuals change over time. Responses from the sample of respondents are generalized to describe changes over time in the population from which the sample was drawn. Problems with longitudinal designs: Just because people change over time, surveys can’t tell us why people change. Attrition occurs when people drop out of the study. Reactivity: Respondents may strive to be consistent or become sensitized to the topic.