CHAPTER 5: Correlation and Quasi - Experimental Design Flashcards

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1
Q

causing or producing the effect.

A

Causation

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2
Q

It is used to establish relationship among preexisting behavior. It can show the relationships between sets of antecedent conditions and behavior.

A

Correlational Design

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3
Q

It is a design that is used to determine the correlation, or degree of relationship, between two traits, behavior, or events.

A

Correlation Study

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4
Q

is any observable behavior, characteristics, or event that can vary or have different values.

A

Variable

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5
Q

It is the relationships between pairs of scores from each subject.

A

Simple Correlation

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6
Q

is the most commonly used procedures for calculating simple correlations.

A

Pearson Correlation Coefficient (r)

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7
Q

shows the scores on one variable plotted against scores on a second variable.

A

Scatterplot

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8
Q

it is the line that is drawn on the scatterplots and it measures scores. The direction of the line corresponds to the direction of relationship (positive or negative).

A

Regression Line (lines of best fit)

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9
Q

Correlation does not imply causation

A

even though a relationship exists between two measures, we cannot say that one causes the other, even when such statement is reasonable.

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10
Q

means a behavior could affect each other.

A

Bidirectional Causation

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11
Q

third agent may actually be causing to behaviors appear to be related.

A

Third Variable Problem

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12
Q

estimates the amount of variability scores on one variable that can be explained by the other variable.

A

Coefficient of Determination

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13
Q

determines the degree of relation between two variables.

A

Multiple Correlation

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14
Q

uses regression equation to predict scores on one variable from scores on the second correlated variable.

A

Linear Regression Analysis

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15
Q

uses regression equation on one variable from scores on sets of other variables.

  • represents “R”
A

Multiple Regression

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16
Q

determines the subsets of correlated variables within a larger set of variable.

A

Factor Analysis

17
Q

uses beta weights from multiple regression analysis to generate possible direction of cause and effect from correlated variables.

A

Path Analysis

18
Q

measures the same pair if variables at two different points in time, looks at patterns of correlation across time for possible direction of cause and effect.

A

Cross-lagged Panel

19
Q
  • after the fact in the effect
  • is a study in which the researcher systematically examines the effects of subject characteristics but without actually manipulating them.
  • capitalizes on changes in the antecedent conditions that occurred before the study.
A

Ex Post Facto

20
Q

are collected for each item or variable for one or more time periods

A

Data

21
Q

involves some comparison of data between or among periods.

A

Analysis

22
Q

investigates changes across time by comparing groups of subjects already at different stage at a “single point” in time.

A

Cross-sectional Study

23
Q

investigates changes occur time by measuring behavior of same group of subjects at different point in time. (long term studies)

A

Longitudinal

24
Q

it is a threat to internal validity are not completely controlled because the comparison group is taken from another population and is unlikely to be equivalent to the treatment group.

A

Non-equivalent control group design

25
Q

it is often used to assess the effect of naturally occurring events when a true experiment is not possible; sometimes such a design is used in a laboratory studies, but it is a number of problems that reduce its internal validity.

A

Pretest-Posttest design

26
Q

a group that took both the pretest and posttest but was not exposed to the “treatment” this design has been called “the old workhorse of traditional experimentation”.

A

Non equivalent control group