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PSY 255 > Chapter 2- Methods and Statistics in I-O Psychology > Flashcards

Chapter 2- Methods and Statistics in I-O Psychology Flashcards

1
Q

Research Design

A

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

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2
Q

Experimental Design

A

Participants are randomly assigned to different conditions

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3
Q

Quasi-experimental Design

A

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

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4
Q

Non-experimental design

A

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

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5
Q

Observational Design

A

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

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6
Q

Survey Design

A

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

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7
Q

Quantitative methods

A

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

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8
Q

Qualitative Methods

A

Rely on observation, interview, case study, and analysis of diaries or written documents and produce flow diagrams and narrative descriptions of events or processes

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9
Q

Introspection

A

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

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10
Q

Triangulation

A

Approach in which researchers seek converging information from different sources.

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11
Q

Generalize

A

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

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12
Q

Experimental Control

A

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 that in field studies.

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13
Q

Statistical Control

A

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

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14
Q

Descriptive Statistics

A

Summarize, organize, and describe a sample of data.

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15
Q

Measure of Central Tendency

A

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

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16
Q

Variability

A

The extent to which scores in a distribution vary

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17
Q

Skew

A

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

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18
Q

Mean

A

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

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19
Q

Mode

A

The most common or frequently occurring score in a distribution

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20
Q

Median

A

The middle score in a distribution

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21
Q

Inferential Statistics

A

Used to aid the researcher in testing hypothesis and making inferences from sample data to a larger sample or population

22
Q

Statistical significance

A

Indicates that the probability of the observed statistic is less than the stated significance level adopted by the researcher (commonly p<_ .05). This finding indicates that, if the null hypothesis were true, the results found are unlikely to occur by chance, and the null hypothesis is rejected

23
Q

Statistical Power

A

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

24
Q

Measurement

A

Assigning numbers to characteristics of individuals or objects according to rules

25
Q

Correlation coefficient

A

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.

26
Q

Scatterplot

A

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

27
Q

Regression Line

A

Straight line that best “fits” the scatterplot and describes the relationship between 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.

28
Q

Linear

A

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

29
Q

Nonlinear

A

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

30
Q

Multiple Correlation Coefficient

A

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.

31
Q

Meta-analysis

A

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

32
Q

Statistical artifacts

A

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

33
Q

Micro-research

A

The study of individual behavior

34
Q

Macro-research

A

The study of collective behavior

35
Q

Meso-research

A

The study of the interaction of individual and collective behavior

36
Q

Reliability

A

Consistency or stability of a measure

37
Q

Validity

A

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

38
Q

Test-retest Reliability

A

Calculated by correlating measurements taken at time one with measurements take time two

39
Q

Equivalent forms reliability

A

Calculated by correlating measurements from a sample of individuals who complete two different forms of the same test

40
Q

Internal consistency

A

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

41
Q

Generalizability theory

A

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)

42
Q

Predictor

A

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

43
Q

Criterion

A

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

44
Q

Criterion-related validity

A

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

45
Q

Validity coefficient

A

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

46
Q

Predictive validity design

A

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

47
Q

Concurrent validity design

A

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

48
Q

Content-related validation design

A

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

49
Q

Construct Validity

A

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

50
Q

Construct

A

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

PSY 255 (2 decks)

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