Correlational Research

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Correlational Research

• 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

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Sex, Romance, and Relationships

• a survey about sexual attitudes and practices

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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

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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.
Best Fit Line
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Scatter Plot of Family Income and Students
average grade
Figure 15.2 page 511 Correlation data showing
the relationship between family income (X) and
student grades (Y) for a sample of n14 high
school students. The scores are listed in order
from lowest to highest family income and are
shown in a scatter plot.
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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.

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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.
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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

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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.
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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.

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Survey Research

• Widely used by Social, Political and
  Psychological scientists
• Surveys are used to
• describe peoples opinions, attitudes, and
  preferences
• make predictions about peoples 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

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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, registrars 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.

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Figure 5.1 Illustration of relationship among
four basic terms in sampling
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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!

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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

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Obtaining a Sample

• Two sources of biased samples
• Selection bias occurs when the researchers
  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 arent
  interested, theyre worried about privacy, have
  vision or other problems, dont have time, etc.
• Final sample will only represent the population
  of people who are interested, not worried, have
  good vision, time, etc.

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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?

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Approaches to Sampling

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

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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?

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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.

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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.

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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 dont 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

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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.

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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

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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

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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.

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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.

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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.

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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 dont 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 dont know if responses differ because
  of true changes over time, or because different
  populations were sampled.

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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
  cant 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.