Ch 2: Research Methods Flashcards

1
Q

All of the following methods are common to all sciences except:

a. Science depends on data.
b. Science sets out to prove theories or hypotheses.
c. Science must be communicable, open, and public.
d. Scientists should be objective and not influenced by biases or prejudices.

A

b. Science sets out to prove theories or hypotheses.

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2
Q

Dr. Groeneveld is not able to include any treatments or conditions in an investigation of a new pay plan. Instead, he is gathering information about the effects of a new pay plan and making systematic observations about changes in performance based on this new pay plan. This type of research would best be classified as a(n)

a. Quasi-experimental design
b. Experimental design
c. Non-experimental design
d. Survey design

A

c. Non-experimental design

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3
Q

Dr. Brown is conducting a scientific experiment and has randomly assigned the participants into two training groups, which receive training programs. What type of research design is Dr. Brown using?

a. Quasi-experimental design
b. Experimental design
c. Non-experimental design
d. Survey design

A

b. Experimental design

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4
Q

In I-O psychology, field studies are often non-experimental in design. All of the following help explain the popularity of non-experimental field studies except:

a. The extent to which a laboratory experiment can reasonably simulate “work” is limited.
b. Laboratory experiments are more likely to use samples that are not representative of the population to which I-O psychologists would like to generalize.
c. Non-experimental designs in the field are most effective in leading to causal explanations.
d. In the field, workers can seldom be randomly assigned to conditions or treatments.

A

c. Non-experimental designs in the field are most effective in leading to causal explanations.

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5
Q

___________ methods rely heavily on tests, rating scales, questionnaires, and physiological measures, while ___________ methods of investigation generally produce flow diagrams and narrative descriptions of events or processes.

a. Objective; Subjective
b. Subjective; Objective
c. Qualitative; Quantitative
d. Quantitative; Qualitative

A

d. Quantitative; Qualitative

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6
Q

Dr. Young is in the process of combining information from multiple sources to test a theory. According to Rogelberg and Brooks-Laber (2002), this approach is referred to as

a. Triangulation
b. Unification
c. Mergence
d. Convergence

A

a. Triangulation

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7
Q

Each of the following is directly related to increasing the extent to the results of a studycan be generalized to a larger population except:

a. Collecting data at several different points in time.
b. Using a representative sample of the population being studied.
c. Making the sample size larger.
d. Collecting data from many different organizations.

A

c. Making the sample size larger.

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8
Q

All of the following are characteristics that can be used to describe a score distribution except:

a. Mean
b. Significance
c. Skew
d. Median

A

b. Significance

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9
Q

Inferential statistics are used to:

a. extrapolate data into the future.
b. compare the results of different analyses.
c. reveal patterns in a set of data.
d. draw a conclusion based on results from sample data.

A

d. draw a conclusion based on results from sample data.

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10
Q

A correlation of r = –.79 indicates that there is a

a. high negative association between two variables.
b. high positive association between two variables.
c. low negative association between two variables.
d. low positive association between two variables.

A

a. high negative association between two variables.

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11
Q

Approach that involves the understanding, prediction, and control of some phenomenon of interest.

A

Science

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12
Q

Prediction about relationship(s) among variables of interest.

A

Hypothesis

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13
Q

Characteristic of scientists, who should be objective and uninfluenced by biases or prejudices when conducting research.

A

Disinterestedness

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14
Q

Witness in a lawsuit who is permitted to voice opinions about organizational practices.

A

Expert witness

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15
Q

Provides the overall structure or architecture for the research study; allows investigators to conduct scientific research on a phenomenon of interest.

A

Research design

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16
Q

Participants are randomly assigned to different conditions.

A

Experimental design

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17
Q

Participants are assigned to different conditions, but random assignment to conditions is not possible.

A

Quasi-experimental design

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18
Q

Does not include any “treatment” or assignment to different conditions.

A

Nonexperimental design

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19
Q

The researcher observes employee behavior and systematically records what is observed.

A

Observational design

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20
Q

Research strategy in which participants are asked to complete a questionnaire or survey.

A

Survey design

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21
Q

Rely on tests, rating scales, questionnaires, and physiological measures and yield numerical results.

A

Quantitative methods

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22
Q

Rely on observations, interviews, case studies, and analysis of diaries or written documents and produce flow diagrams and narrative descriptions of events or processes.

A

Qualitative methods

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23
Q

Early scientific method in which the participant was also the experimenter, recording his or her experiences in completing an experimental task; considered very subjective by modern standards.

A

Introspection

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24
Q

Approach in which researchers seek converging information from different sources.

A

Triangulation

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25
Q

To apply the results from one study or sample to other participants or situations.

A

Generalize

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26
Q

Characteristic of research in which possible confounding influences that might make results less reliable or harder to interpret are eliminated; often easier to establish in laboratory studies than in field studies.

A

Experimental control

27
Q

Using statistical techniques to control for the influence of certain variables. Such control allows researchers to concentrate exclusively on the primary relationships of interest.

A

Statistical control

28
Q

Statistics that summarize, organize, and describe a sample of data.

A

Descriptive statistics

29
Q

Statistic that indicates where the center of a distribution is located. Mean, median, and mode are measures of central tendency.

A

Measure of central tendency

30
Q

The extent to which scores in a distribution vary.

A

Variability

31
Q

The extent to which scores in a distribution are lopsided or tend to fall on the left or right side of the distribution.

A

Skew

32
Q

The arithmetic average of the scores in a distribution; obtained by summing all of the scores in a distribution and dividing by the sample size.

A

Mean

33
Q

The most common or frequently occurring score in a distribution.

A

Mode

34
Q

The middle score in a distribution.

A

Median

35
Q

Statistics used to aid the researcher in testing hypotheses and making inferences from sample data to a larger sample or population.

A

Inferential statistics

36
Q

Indicates that the probability of the observed statistic is less than the stated significance level adopted by the researcher (commonly p < .05). A statistically significant finding indicates that the results found are unlikely to have occurred by chance, and thus the null hypothesis (i.e., hypothesis of no effect) is rejected.

A

Statistical significance

37
Q

The likelihood of finding a statistically significant difference when a true difference exists.

A

Statistical power

38
Q

Assigning numbers to characteristics of individuals or objects according to rules.

A

Measurement

39
Q

Statistic assessing the bivariate, linear association between two variables. Provides information about both the magnitude (numerical value) and the direction (􏰂 or 􏰃) of the relationship between two variables.

A

Correlation coefficient

40
Q

Graph used to plot the scatter of scores on two variables; used to display the correlational relationship between two variables.

A

Scatterplot

41
Q

Straight line that best “fits” the scatterplot and describes the relationship between the variables in the graph; can also be presented as an equation that specifies where the line intersects the vertical axis and what the angle or slope of the line is.

A

Regression line

42
Q

Relationship between two variables that can be depicted by a straight line.

A

Linear

43
Q

Relationship between two variables that cannot be depicted by a straight line; sometimes called “curvilinear” and most easily identified by examining a scatterplot.

A

Nonlinear

44
Q

Statistic that represents the overall linear association between several variables (e.g., cognitive ability, personality, experience) on the one hand and a single variable (e.g., job performance) on the other hand.

A

Multiple correlation coefficient

45
Q

Statistical method for combining and analyzing the results from many studies to draw a general conclusion about relationships among variables.

A

Meta-analysis

46
Q

Characteristics (e.g., small sample size, unreliable measures) of a particular study that distort the observed results. Researchers can correct for artifacts to arrive at a statistic that represents the “true” relationship between the variables of interest.

A

Statistical artifacts

47
Q

The study of individual behavior.

A

Micro-research

48
Q

The study of collective behavior.

A

Macro-research

49
Q

The study of the interaction of individual and collective behavior.

A

Meso-research

50
Q

Consistency or stability of a measure.

A

Reliability

51
Q

The accuracy of inferences made based on test or performance data; also addresses whether a measure accurately and completely represents what was intended to be measured.

A

Validity

52
Q

A type of reliability calculated by correlating measurements taken at time 1 with measurements taken at time 2.

A

Test–retest reliability

53
Q

A type of reliability calculated by correlating measurements from a sample of individuals who complete two different forms of the same test.

A

Equivalent forms reliability

54
Q

Form of reliability that assesses how consistently the items of a test measure a single construct; affected by the number of items in the test and the correlations among the test items.

A

Internal consistency

55
Q

A sophisticated approach to the question of reliability that simultaneously considers all types of error in reliability estimates (e.g., test-retest, equivalent forms, and internal consistency).

A

Generalizability theory

56
Q

The test chosen or developed to assess attributes (e.g., abilities) identified as important for successful job performance.

A

Predictor

57
Q

An outcome variable that describes important aspects or demands of the job; the variable that we predict when evaluating the validity of a predictor.

A

Criterion

58
Q

Validity approach that is demonstrated by correlating a test score with a performance measure; improves researcher’s confidence in the inference that people with higher test scores have higher performance.

A

Criterion-related validity

59
Q

Correlation coefficient between a test score (predictor) and a performance measure (criterion).

A

Validity coefficient

60
Q

Criterion-related validity design in which there is a time lag between collection of the test data and the criterion data.

A

Predictive validity design

61
Q

Criterion-related validity design in which there is no time lag between gathering the test scores and the performance data.

A

Concurrent validity design

62
Q

A design that demonstrates that the content of the selection procedure represents an adequate sample of important work behaviors and activities and/or worker KSAOs defined by the job analysis.

A

Content-related validation design

63
Q

Validity approach in which investigators gather evidence to support decisions or inferences about psychological constructs; often begins with investigators demonstrating that a test designed to measure a particular construct correlates with other tests in the predicted manner.

A

Construct validity

64
Q

Psychological concept or characteristic that a predictor is intended to measure; examples are intelligence, personality, and leadership.

A

Construct