Research Methods In Psychology Test 5

Front 1

In this type of design the researcher lacks control over the assignment of participants to conditions and/or does not manipulate the causal variable of interest.

Back 1

Quasi-Experimental Design

Front 2

Not a true independent variable, but rather an event that occurred for other reasons.

Back 2

Quasi-Experimental Variable.

Front 3

Quasi-experimental designs to not have as high of __________ as true experimental designs.

Back 3

Internal Validity.

Front 4

Two basic facts of quasi-experimental designs.

Back 4

1) Lack of ability to randomly assign participants
2) Lack of ability to manipulate the independent variable.

Front 5

This design fails to eliminate most threats to internal validity.

Back 5

One-Group Pretest-PostTest design.

Front 6

The tendency for extreme scores in a distribution to move, or regress, toward the mean of the distribution with repeated testing.

Back 6

Regression to the mean.

Front 7

One group pretest-postest design should be considered _______________rather than quasi-experimental design because it lacks control, has no internal validity and fails to meet research design at all.

Back 7

Preexperimental design
(referring to one group pretest-postest design).

Front 8

The researcher looks for one or more groups of participants that appear to be reasonably similar to the group that received the quasi-independent variable.

Back 8

Nonequivalent control groups design.

Front 9

This option measures both groups after one of them has received the quasi-experimental design

Back 9

Non-equivalent groups posttest design.

Front 10

When participants in different conditions interact with one another.

Back 10

Experimental Contamination.

Front 11

When something happens to one group that does not happen to another group

Back 11

Local History Effect.

Front 12

Confound due to local history effect.

Back 12

Selection by history interaction.

Front 13

Measure the dependent variable on several occasions before and on several occasions after the quasi-independent variable occurs.

Back 13

Time Series Design

Front 14

Taking several pretest measures before introducing the independent variable and then several postest measures

Back 14

Simple interrupted times series design

Front 15

A central threat to internal validity with simple interrupted times series design is:

Back 15

Contemporary History

Front 16

When the quasi-experimental variable or treatment is first introduced, then removed.

Back 16

Interrupted time series design with a reversal.

Front 17

Introduce the variable, remove it, then re-introduce it again.

Back 17

Interrupted time series design with multiple replications.

Front 18

Examines two or more variables over time in order to understand how changes in one variable are related to changes in another variable.

Back 18

Comparative time series design.

Front 19

In the case of _____________, the quasi-independent variable is time itself.

Back 19

Longitudinal Designs.

Front 20

Designs that compare groups of different ages at a single point in time.

Back 20

Cross-sectional Design.

Front 21

Put simply people of different ages differ not only in age per se, but also in the conditions which they grew up.

Back 21

Generational Effects.

Front 22

Uses behavioral research methods to assess the effects of interventions (or programs) designed to influence behavior.

Back 22

Program evaluation.

Front 23

Argues that researchers should critically consider many ways of obtaining evidence relevant to a particular hypothesis and then employ several different approaches

Back 23

Critical Multiplism

Front 24

__________ analysis are often used to extend the findings of correlational research.

Back 24

Regression Analyses

Front 25

____________ provide us with a mathematical description of how the variables are related and allow us to predict one variable from the others.

Back 25

Regression Equation

Front 26

The ability to predict scores on one variable from one or more other variables is accomplished through _____________.

Back 26

Regression Analysis

Front 27

The goal of regression analysis is to develop a _________________ from which we can predict one score on the basis of one or more other scores.

Back 27

Regression Equation

Front 28

Correlation indicates a __________ relationship between two variables.

Back 28

Linear.

Front 29

What is the equation for linear regression?

Back 29

y = Bo + B1x

Front 30

In the regression equation what is the variable we would like to predict?

Back 30

Y

Front 31

The variable we want to predict is the __________.

Back 31

Dependent Variable.

Front 32

Which is the variable we are using to predict y?

Back 32

x

Front 33

What is another term for x?

Back 33

Predictor Variable.

Front 34

Bo is known as the ________.

Back 34

Regression Constant.

Front 35

What is Bo, mathematically speaking in the regression equation?

Back 35

The Y-Intercept.

Front 36

What is B1 in the regression equation?

Back 36

The regression coefficient
(the slope of the line)

Front 37

What does the regression coefficient represent?

Back 37

The slope of the line.

Front 38

Using ____________, you could develop a regression equation that includes multiple predictors.

Back 38

Multiple Regression Analysis.

Front 39

What are the 3 types of multiple regression analyses?

Back 39

1) Standard
2) Stepwise
3) Hierarchical

Front 40

In ___________ all of the predictor variables are entered into the regression analysis at the same time.

Back 40

Standard Mulitple Regression.

Front 41

Rather than entering all the predictors at once, ____________ analysis builds the regression equation by entering the predictor variables one at a time.

Back 41

Stepwise Multiple Regression

Front 42

In _________________, the predictor variables are entered into the equation in an order that is predetermined by researchers, based on hypotheses that they want to test.

Back 42

Hierarchical Mulitple Regression.

Front 43

To express the usefulness of a regression equation for predicting, researchers calculate the __________

Back 43

Multiple Correlation Coefficient (R)

Front 44

The range of R is:

Back 44

.00-1.00

Front 45

Refers to a class of statistical techniques that are used to analyze the interrelationships among a large number of variables.

Back 45

Factor Analysis.

Front 46

3 uses of factor analysis

Back 46

1) To study the underlying structure of psychological constructs.
2) to reduce a large number of variables to a smaller, more manageable set of data.
3) Used in the development of self-report measures of attitudes and personality.

Front 47

Refers to the practice of relying on observation to draw conslusions about the world.

Back 47

Empiricism

Front 48

We use this to determine whether the observed difference between the means of experimental conditions is greater than expected based on error alone.

Back 48

Inferential Statistics

Front 49

States that the independent variable did not have an effect on the dependent variable.

Back 49

Null Hypothesis

Front 50

Define Type I Error:

Back 50

Rejecting the null hypothesis when it is true.

Front 51

Define Type II Error:

Back 51

Failing to reject the null hypothesis when it is false.

Front 52

The probability that a study will correctly reject the null hypothesis when it is false.

Back 52

Power

Front 53

Determines the number of participants needed to detect the effect of the independent variable.

Back 53

Power Analysis.

Front 54

Defines a concept by specifying precisely how the concept is measured or manipulated in a study.

Back 54

Operational Definition.

Front 55

Used to integrate the results from a large set of individual studies.

Back 55

Meta Analysis.

Front 56

How and why behavior varies across situations, differs among individuals, and changes over time.

Back 56

Behavioral Variability.

Front 57

The consistency or dependability of a measuring technique; is inversely proportional to measurement error.

Back 57

Reliability

Front 58

The extent to which a measurement procedure actually measures what it is intended to measure.

Back 58

Validity

Front 59

A method of collecting data in which participants record information about their thoughts, emotions, or behaviors as they occur in everyday life.

Back 59

Experience Sampling Method (ESM)

Front 60

The observation of behavior in settings that have been arranged specifically for observation and recording of behavior.

Back 60

Contrived Observation

Front 61

Observation of on-going behavior as it occurs naturally with no intrusion or intervention by the researcher.

Back 61

Naturalistic Observation

Front 62

Observing participants' behavior without their knowledge.

Back 62

Disguised Observation

Front 63

A statistic that expresses how much a particular participant's score varies from the mean in terms of standard deviations: also called the standard score.

Back 63

Z-Score

Front 64

Descriptive statistics that convey information about the average or typical score in a distribution; the mean, median and mode.

Back 64

Measures of Central Tendency

Front 65

An experiment in which participants' responses are measured twice, once before and once after the introduction of the independent variable.

Back 65

Pre-Post Design

Front 66

An experiment in which two or more independent variables are maniupulated.

Back 66

Factorial Design

Front 67

(Written) In the regression equation:

y=5.00 - .42x, what are x and y?

Back 67

x is the predictor variable, what we are using to determine y

y is the dependent variable, the variable we are trying to predict.

Front 68

(Written) Imagine you conduct a multiple regression analysis in which you have four predictor variables. The multiple correlation coefficient from this analysis is .50. Explain what this tells you.

Back 68

-The correletion coefficient, symbolized by (R) describes the degree of relationship between: The criterion variable (y) and the set of predictor variables. If the correlation coefficient is .5 than R-squared gives .25 or 25% of the variance in the participants' dependent variable scores are accounted for by the set of four predictor variables.

Front 69

(Written) What are the three primary uses of factor analysis?

Back 69

1) Used to study the underlying structure of psychological constructs
2) Reduces large number of variables to a smaller, more manageable set of data
3) Factor Analysis is commonly used in the development of self-report measures of attitudes and personality.

Front 70

(Written) How do quasi-experimental designs differ from true experiemental designs?

Back 70

-In quasi-experimental designs, the researcher lacks control over the assignment of participants to conditions or cannot manipulate the independent variable.

Front 71

(Written) What three criteria must be met to establish that a particular variable causes certain behavioral effects?

Back 71

1) The presumed causal variable preceeded the effect in time.
2) The cause and effect covary.
3) All other alternative explanations of the results are eliminated through randomization or experimental control.

Front 72

(Written) What is program evaluation?

Back 72

Concept that uses behavioral research methods to assess the effects of interventions (or programs) designed to influence behavior.

Front 73

(Written) Why do program evaluators frequently rely on program evaluation?

Back 73

Because these kinds of programs are not usually under researchers' control, they must use quasi-experimental approaches to evaluate their effectiveness.