Research Methods Exam

Front 1

Why are surveys important?

Back 1

-“snapshot” of how people think at a certain point in time
-study relationships among variables
-ways that attitudes change over time
-compliment experimental research findings

Front 2

Response set

Back 2

a tendency to respond to all questions from a particular perspective rather than to provide answers that are directly related to the questions
*can affect usefulness of data obtained from self-reports

Front 3

Social desirability

Back 3

response set that leads the individual to answer in the most socially acceptable way

Front 4

When are people most likely to lie on a survey, and how can this be avoided?

Back 4

when they don’t trust the researcher

researcher needs to:
-openly and honestly communicate the purposes and uses of the research
-promise to provide feedback about the results
-assure confidentiality

Front 5

What are the major considerations in survey research?

Back 5

-constructing the questions that are asked
-choosing the methods for presenting the question
-sampling the individuals taking part of the research

Front 6

What are the three general types of survey questions?

Back 6

-attitudes & beliefs
-facts & demographics
-behaviours

Front 7

What are the potential problems with question wording on a survey?

Back 7

-difficulty understanding Q
-unfamiliar, vague or imprecise terms,
-bad grammar
-complex phrasing,
-embedding Q with misleading info

Front 8

What is important to consider with question wording?

Back 8

-simplicity, loaded questions, negative wording, yes/nay saying

Front 9

How does a researcher construct the questions to ask on a survey?

Back 9

-define research objectives
-type of questions to ask
-question wording

Front 10

What are the two basic sampling techniques?

Back 10

probability and nonprobability sampling.

Front 11

probability sampling

Back 11

each member of the population has a specifiable probability of being chosen

Front 12

nonprobability sampling

Back 12

we don't know the probability of any particular member of the population being chosen

Front 13

What are the three types of probability sampling?

Back 13

simple random sampling, stratified random sampling, cluster sampling

Front 14

simple random sampling

Back 14

every member of the population has an equal probability of being selected

Front 15

stratified random sampling

Back 15

population is divided into subgroups (strata) and random sampling techniques are then used to select sample members from each stratum. (age, gender, education, etc)

Front 16

cluster sampling

Back 16

researcher identifies "clusters" of individuals and then sample from these clusters. (ex: list all classes being taught and randomly sample each class)

Front 17

What are three types of nonprobability sampling?

Back 17

haphazard sampling, purposive sampling, and quota sampling

Front 18

haphazard sampling

Back 18

(aka convenience) take them where you find them

Front 19

purposive sampling

Back 19

obtaining a sample of people who meet some predetermined criterion

Front 20

quota sampling

Back 20

choosing a sample that reflects the numerical composition of various subgroups in the population

Front 21

how do you create a completely unbiased sample of a population?

Back 21

-randomly sample from the whole population
-contact and obtain responses from all individuals in the population

Front 22

what are the two sources of biases in random sampling?

Back 22

the sampling frame used and poor response rates

Front 23

sampling frame

Back 23

the actual population of individuals (or clusters) from which a random sample will be drawn

Front 24

response rate

Back 24

the percentage of people in the sample who actually complete the survey

Front 25

How can you maximize the response rate of a mail survey?

Back 25

-explanatory postcard before survey is mailed
-follow-up reminders
-second mailing of questionnaire
-personally stamped return envelope
-look of cover page

Front 26

How can you maximize the response rate of a telephone survey?

Back 26

-no answer = call again
-reschedule those who can't interview at the time
-offer incentive
-convince importance and value of participation

Front 27

Why use a convenience sample?

Back 27

-low cost/time selecting sample
-research is studying relationships between variables, rather than accurately estimating

Front 28

Panel study

Back 28

when the same people are surveyed at two or more points in time

Front 29

What does a researcher need to consider about responses to questions?

Back 29

-closed vs open ended
-number of response alternatives
-rating scales
-labelling response alternatives

Front 30

What are the types of rating scales (surveys)?

Back 30

-graphic (agree/disagree)
-semantic differential scale (good/bad)
-nonverbal scale for children

Front 31

How does a researcher finalize the questionnaire?

Back 31

-format whole thing and refine Q’s (pilot study)

Front 32

What are the two main ways to administer a survey?

Back 32

-written or interview

Front 33

What are the four types of questionnaires?

Back 33

-personal admin to groups or individuals
-mail surveys
-internet surveys
-other tech

Front 34

What are the advantages/disadvantages of questionnaires?

Back 34

- less costly, completely anonymous.
- Respondent needs to be able to read/understand, can be boring (motivation)

Front 35

interviewer bias

Back 35

all of the biases that can arise because interviewer is a human)

Front 36

What are the advantages/disadvantages of interviews?

Back 36

-interaction=important;more likely to agree to answer Q’s + can clarify questions and follow up on answers that need expansion
-interviewer bias

Front 37

How can you minimize interviewer bias?

Back 37

careful screening of interviewer

Front 38

What are the three methods of conducting interviews?

Back 38

1. Face-to-face
2. Telephone
3. focus group interviews

Front 39

confidence interval

Back 39

An interval of values within which there is a given level of confidence (e.g., 95%) where the population value lies.

Front 40

sampling error

Back 40

margin of error

Front 41

CATI

Back 41

computer assisted telephone interviewing

Front 42

What are two reasons for using statistics?

Back 42

-describe the data
-make inferences

Front 43

What do you do if you don't know whether an ordinal or interval scale is being used? why?

Back 43

Assume interval scale because it allows for more sophisticated statistical treatment

Front 44

Depending on the way a variable is being studied, what are the three basic ways of describing the results?

Back 44

-comparing group percentages
-correlating scores of individuals on two variables
-comparing group means

Front 45

frequency distribution

Back 45

indicates the number of individuals that receive each possible score on a variable (ex: exam score)

Front 46

What are some ways to graphically depict frequency distributions?

Back 46

-pie chart
-bar graph
-frequency polygon

Front 47

frequency polygon

Back 47

uses a line to represent frequencies (most useful with interval or ratio scales)

Front 48

histogram

Back 48

uses bars to display a frequency distribution for a quanittative variable

Front 49

What can you discover by examining frequency distributions?

Back 49

-directly observe participants' responses
-see what scores are most frequent
-look at the shape of the distribution of scores
-can tell whether there are any outliers (unusual/unexpected/different)
-compare distribution of scores between groups

Front 50

descriptive statistics

Back 50

allow researchers to make precise statements about data

Front 51

what two statistics are needed to describe data?

Back 51

-central tendency (single number.. how participants scored overall)
-variability (how widely the distribution of scores was spread)

Front 52

central tendency

Back 52

tells us what the sample as a whole is like (average)

Front 53

what are the three measures of central tendency?

Back 53

mean, median, mode

Front 54

mean

Back 54

average (M)
-interval or ratio

Front 55

median

Back 55

the score that divides the group in half (Mdn)
-ordinal

Front 56

mode

Back 56

most frequent score
-nominal

Front 57

variability

Back 57

a number that characterizes the amount of spread in a distribution of scores

Front 58

standard deviation

Back 58

the average deviation of scores from the mean

Front 59

correlation coefficient

Back 59

statistic that describes how strongly variables are related to one another

Front 60

What causes the problem of restricted range?

Back 60

when the individuals in a sample are very similar (homogenous)

Front 61

effect size

Back 61

general term that refers to the strength of association between variables

Front 62

regression equation

Back 62

used to predict a person's score on one variable when that person's score on another variable is already known

Front 63

multiple correlation

Back 63

technique used to combine a number of predictor variables to increase the accuracy of prediction of a given criterion or outcome variable

Front 64

partial correlation

Back 64

statistically controls third variables by removing its influence with an equation

Front 65

what are the two forms of basic experimental design?

Back 65

-post-test only
-pre-test post-test

Front 66

posttest-only design must:

Back 66

-obtain two equal groups of participants
-introduce the independent variable
-measure the effect of IV on DV

Front 67

pretest-posttest design

Back 67

same as posttest-only but test is given before and after manipulation

Front 68

independent groups design

Back 68

when participants are randomly assigned to the various conditions and each is only in one group

Front 69

repeated measures design

Back 69

participants are in all conditions

Front 70

what are the advantages/disadvantages of repeated measure design?

Back 70

-fewer participants are needed
-extremely sensitive to finding statistically significant differences between groups
-disadv: one must come before the other

Front 71

order effect

Back 71

when the order of presenting the treatments affects the dependent variable

Front 72

what are some types of order effects?

Back 72

-practice effect (improvement)
-fatigue effect
-contrast effect (comparing them)

Front 73

what are the two approaches to dealing with order effects?

Back 73

-counterbalancing
-long interval between conditions

Front 74

complete counterbalancing

Back 74

when all possible orders of presentation are included in the experiment

Front 75

latin square

Back 75

limited set of orders constructed to ensure that
-each condition appears at each ordinal position
-each condition precedes and follows each condition one time

Front 76

what are the two major advantages of repeated measures designs over independent groups?

Back 76

-less participants needed
-more control over participant differences, thus greater ability to detect effect of IV

Front 77

matched pairs design

Back 77

matching people on a participant characteristic and putting them in different groups

Front 78

what are three experimental designs?

Back 78

-independent groups design
-repeated measures design
-matched pairs design

Front 79

selection differences

Back 79

Differences in the type of subjects who make up each group in an experimental design; this situation occurs when participants elect which group they are to be assigned to.

Front 80

What are the advantages/disadvantages of pretest-posttest design?

Back 80

-assess whether groups were equal to begin with
-participant selection
-measure the extent of change in individual
-necessary when there is a possibility that participants will drop out (mortality)
-disadv: time consuming and awkward to administer
-sensitise participants to what you are studying

Front 81

How can you directly assess the impact of the pretest?

Back 81

-combination of post-test and pretest only design

Front 82

what are the two things you usually have to do when "setting the stage" for an experiment?

Back 82

-provide the participants with the informed consent info needed
-explain why the experiment is being conducted

Front 83

what are the two types of manipulations?

Back 83

straightforward and staged

Front 84

straightforward manipulation

Back 84

manipulate variables with instructions and stimulus presentations

Front 85

staged manipulation

Back 85

staging events that occur during the experiment

Front 86

when are staged manipulations more frequently used?

Back 86

-when trying to create a psychological state in the participants
-simulate a situation that occurs in the real world

Front 87

what needs to be taken into consideration before using the strongest manipulation possible?

Back 87

-may involve a situation that rarely/never occurs in the real world
-ethics

Front 88

what are the three general types of dependent variables?

Back 88

-self-report
-behavioural
-physiological

Front 89

what are the different ways of measuring behaviour?

Back 89

-rate
-reaction time
-duration

Front 90

functional MRI

Back 90

areas of the brain can be scanned while participant performs a physical or cognitive task

Front 91

sensitivity of the dependent variable

Back 91

The ability of a measure to detect differences between groups.

Front 92

ceiling effect

Back 92

independent variable seems to have no effect on the DV because participants quickly reach the maximum performance level

Front 93

floor effect

Back 93

a task is so difficult that hardly anyone can perform it well

Front 94

What are some considerations when choosing measures?

Back 94

-type of measure
-sensitivity of dependent variable
-multiple measures
-cost
-ethics

Front 95

demand characteristic

Back 95

any feature of an experiment that might inform participants of the purpose of the study

Front 96

how can you control for demand characteristics?

Back 96

-deception
-filler items
-asking participants what they think the research is about
-field/observational (don't know being studied)

Front 97

balanced placebo design

Back 97

-expect-get
-expect-don't get
-don't expect-get
-don't expect-don't get

Front 98

experimenter bias/expectancy effects

Back 98

-experimenters may develop expectations about how participants should respond
-may occur whenever experimenter knows which condition the participants are in

Front 99

what are the two potential sources of experimenter bias?

Back 99

-unintentionally treating participants differently
-subtle differences in the way behaviour is recorded

Front 100

teacher expectancy

Back 100

when teacher's expectations influence student's performance

Front 101

what are some solutions to the expectancy problem?

Back 101

-well trained experimenters, practice
-run all conditions simultaneously
-automated procedures
-experimenters unaware

Front 102

single-blind

Back 102

participant is unaware of which group they are in

Front 103

double blind experiment

Back 103

neither the participant or the experimenter know which group the participant is in

Front 104

what are some other factors that a researcher considers when planning a study?

Back 104

-research proposal
-pilot studies
-manipulation checks
-debriefing

Front 105

manipulation check

Back 105

an attempt to directly measure whether the independent variable manipulation has the intended effect on the participants

Front 106

what are the two advantages of manipulation checks?

Back 106

-saves the expense of running the experiment if manipulation ineffective
-if no significant results

Front 107

what are the steps to conducting an experiment?

Back 107

-selecting research participants
-manipulating the independent variable
-measuring the dependent variable
-additional controls and considerations
-analyzing and interpreting results
-communicating research to others

Front 108

why might a researcher want to design an experiment with three or more levels of an independent variable?

Back 108

-two levels can't provide very much information about exact form of relationship
-can detect curvelinear relationships
-interested in comparing more than two groups

Front 109

factorial designs

Back 109

-designs with more than one independent variable
-all levels of each IV are combined with all levels of the other IV's

Front 110

what two kinds of information do factorial designs yield?

Back 110

-main effect
-interaction

Front 111

main effect

Back 111

information about the effect of each independent variable taken by itself

Front 112

interaction

Back 112

when one IV depends on the particular level of the other IV

Front 113

IV x PV design

Back 113

-type of factorial design
-independent variable x participant variable

Front 114

moderator variable

Back 114

influences the relationship between two other variables (ex: credibility)

Front 115

what are the 5 main points of ethics?

Back 115

Justice, Respect and Dignity, Fidelity and Responsibility, Integrity, Benefience and NonMalefience

Front 116

Alternative Explanation

Back 116

Part of causal inference; a potential alternative cause of an observed relationship between variables.

Front 117

Autonomy (Belmont Report)

Back 117

Principle that individuals in research investigations are capable of making a decision of whether to participate.

Front 118

Beneficence (Belmont Report)

Back 118

Principle that research should have beneficial effects while minimizing any harmful effects.

Front 119

Case Study

Back 119

A descriptive account of the behavior, past history, and other relevant factors concerning a specific individual.

Front 120

Coding System

Back 120

A set of rules used to categorize observations.

Front 121

Concurrent Validity

Back 121

The construct validity of a measure is assessed by examining whether groups of people differ on the measure in expected ways.

Front 122

Content Analysis

Back 122

Systematic analysis of the content of written records.

Front 123

Construct Validity

Back 123

The degree to which a measurement device accurately measures the theoretical construct it is designed to measure.

Front 124

Convergent Validity

Back 124

The construct validity of a measure is assessed by examining the extent to which scores on the measure are related to scores on other measures of the same construct or similar constructs.

Front 125

Correlation Coefficient

Back 125

An index of how strongly two variables are related to each other.

Front 126

Covariation of Cause and Effect

Back 126

Part of causal inference; observing that a change in one variable is accompanied by a change in a second variable.

Front 127

Criterion-oriented validity

Back 127

Techniques for determining construct validity that rely on assessing the relationship between scores on the measure and a criterion or outcome.

Front 128

Cronbach’s Alpha

Back 128

An indicator of internal consistency reliability assessed by examining the average correlation of each item (question) in a measure with every other question.

Front 129

Discriminant Validity

Back 129

The construct validity of a measure is assessed by examining the extent to which scores on the measure are not related to scores on conceptually unrelated measures.

Front 130

External Validity

Back 130

The degree to which the results of an experiment may be generalized.

Front 131

Internal Consistency Validity

Back 131

Reliability assessed with data collected at one point in time with multiple measures of a psychological construct. A measure is reliable when the multiple measures provide similar results.

Front 132

Interval Scale

Back 132

A scale of measurement in which the intervals between numbers on the scale are all equal in size.

Front 133

Justice (Belmont Report)

Back 133

Principle that all individuals and groups should have fair and equal access to the benefits of research participation as well as potential risks of research participation.

Front 134

Measurement Error

Back 134

The degree to which a measurement deviates from the true score value.

Front 135

Nominal Scale

Back 135

A scale of measurement with two or more categories that have no numerical (less than, greater than) properties.

Front 136

Ordinal Scale

Back 136

A scale of measurement in which the measurement categories form a rank order along a continuum.

Front 137

Ratio Scale

Back 137

A scale of measurement in which there is an absolute zero point, indicating an absence of the variable being measured. An implication is that ratios of numbers on the scale can be formed (generally, these are physical measures such as weight or timed measures such as duration or reaction time).

Front 138

Reactivity

Back 138

A problem of measurement in which the measure changes the behavior being observed.

Front 139

Split-half reliability

Back 139

A reliability coefficient determined by the correlation between scores on half of the items on a measure with scores on the other half of a measure.

Front 140

Systematic Observation

Back 140

Observations of one or more specific variables, usually made in a precisely defined setting.

Front 141

Temporal Precedence

Back 141

Part of causal inference; the cause precedes the effect in a time sequence.

Front 142

baseline

Back 142

In a single case design, the subject's behavior during a control period before introduction of the experimental manipulation.

Front 143

cohort

Back 143

A group of people born at about the same time and exposed to the same societal events; cohort effects are confounded with age in a cross-sectional study.

Front 144

control series design

Back 144

An extension of the interrupted time series quasi-experimental design in which there is a comparison or control group.

Front 145

cross-sectional method

Back 145

A developmental research method in which persons of different ages are studied at only one point in time; conceptually similar to an independent groups design.

Front 146

history effect

Back 146

As a threat to the internal validity of an experiment, refers to any outside event that is not part of the manipulation that could be responsible for the results.

Front 147

instrument decay

Back 147

As a threat to internal validity, the possibility that a change in the characteristics of the measurement instrument is responsible for the results.

Front 148

interrupted time series design

Back 148

a design in which the effectiveness of a treatment is determined by examining a series of measurements made over an extended time period both before and after the treatment is introduced. The treatment is not introduced at a random point in time

Front 149

longitudinal method

Back 149

A developmental research method in which the same persons are observed repeatedly as they grow older; conceptually similar to a repeated measures design.

Front 150

maturation effect

Back 150

As a threat to internal validity, the possibility that any naturally occurring change within the individual is responsible for the results.

Front 151

multiple baseline design

Back 151

Observing behavior before and after a manipulation under multiple circumstances (across different individuals, different behaviors, or different settings).

Front 152

nonequivalent control group design

Back 152

A quasi-experimental design in which nonequivalent groups of subjects participate in the different experimental groups, and there is no pretest.

Front 153

nonequivalent control group pretest-posttest design

Back 153

A quasi-experimental design in which nonequivalent groups are used, but a pretest allows assessment of equivalency and pretest-posttest changes.

Front 154

one-group posttest-only design

Back 154

A quasiexperimental design that has no control group and no pretest comparison; a very poor design in terms of internal validity.

Front 155

one-group pretest-posttest design

Back 155

A quasiexperimental design in which the effect of an independent variable is inferred from the pretest-posttest difference in a single group.

Front 156

quasi-experimental design

Back 156

A type of design that approximates the control features of true experiments to infer that a given treatment did have its intended effect.

Front 157

regression toward the mean

Back 157

Also called statistical regression; principle that extreme scores on a variable tend to be closer to the mean when a second measurement is made.

Front 158

reversal design

Back 158

A single case design in which the treatment is introduced after a baseline period and then withdrawn during a second baseline period. It may be extended by adding a second introduction of the treatment. Sometimes called a "withdrawal" design.

Front 159

sequential method

Back 159

A combination of the cross-sectional and longitudinal design to study developmental research questions.

Front 160

testing effect

Back 160

A threat to internal validity in which taking a pretest changes behavior without any effect on the independent variable.

Front 161

conceptual replication

Back 161

Replication of research using different procedures for manipulating or measuring the variables.

Front 162

experimental realism

Back 162

The extent to which the independent variable manipulation has an impact on and involves subjects in an experiment.

Front 163

meta-analysis

Back 163

A set of statistical procedures for combining the results of a number of studies in order to provide a general assessment of the relationship between variables.

Front 164

mundane realism

Back 164

The extent to which the independent variable manipulation is similar to events that occur in the real world.