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Psychology > Experimental Psychology Midterms > Flashcards

Experimental Psychology Midterms Flashcards

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1
Q

The degree of relationship between 2 traits, behaviors, or events

A

Correlation

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2
Q

What are the purposes when measuring correlation?

A
  • To explore behaviors that are not yet understood
  • To study observable characteristics that can take on different values
  • To make predictions about behaviors
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3
Q

Which levels of measurement can correlation be applied to?

A

Interval to Ratio level

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4
Q

This is the coefficient that results from a statistical measure of correlation

A

Pearson Product Moment Correlation

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5
Q

The statistical formulas for this type of correlation use a General Linear Model

A

Simple Correlation

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6
Q

What are the 4 things correlation can determine?

A
  1. Direction of relationship
  2. Strength of relationship
  3. Coefficient of determination
  4. Scatterplot
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7
Q

What is the difference between a negative and positive relationship?

A

Positive means as variable 1 increases, variable 2 also increases. Negative means as variable 1 increases, variable 2 decreases or vice versa

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8
Q

True or False: the nearer the r is to 1, the weaker the relationship

A

False

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9
Q

This is determined by r squared, it is the proportion of shared common variance between 2 variables

A

Coefficient of Determination

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10
Q

This is a graphic representation of the relationship between 2 variables

A

Scatterplot

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11
Q

True or False: a perfect correlation also indicates a causal relationship

A

False

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12
Q

True or False: the regression line goes through most points on the graph

A

True

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13
Q

This is the estimate of a score on one of the measured behaviors based on the score from the other

A

Linear Regression

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14
Q

This is the mathematical equation that best describes the linear relationship between 2 scores

A

Regression Line

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15
Q

This tests the relationship between 3 or more predictor variables with a criterion variable

A

Multiple Correlation

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16
Q

This predicts the scores of criterion variables based on one variable from scores on sets of other predictor variables

A

Multiple Regression

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17
Q

True or False: multiple regression only requires 1 predictor variable

A

False, it requires at least 2

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18
Q

This shows the weight or degree of influence of each predictor variable

A

Beta Weights

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19
Q

This is a multiple regression design where subjects are measured on several related behaviors and causal sequences for these behaviors are established

A

Path Analysis

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20
Q

This multiple regression design measures several related characteristics on two separate points in time. It is based on correlation

A

Cross-lagged Panel Design

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21
Q

These are study designs that resemble but are not classified as experimental designs

A

Quasi-experimental Designs

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22
Q

True or False: random assignment is recommended for quasi-experimental studies

A

False, it is not possible to do random assignment

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23
Q

What is the level of internal validity of quasi-experimental designs?

A

Low Internal Validity

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24
Q

If experimental designs are based on controlled treatments, quasi designs are based on?

A

Pre-existing conditions/naturally occurring events

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25
Q

If both quasi designs and correlation study different groups of subjects, how do they differ from each other?

A

Quasi designs focus on studying how results change over time in the same group, while correlation studies relationships and associations between them

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26
Q

This is a quasi-experimental design where subjects are grouped based on characteristics that already exist (i.e race, education)

A

Ex Post Facto Studies

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27
Q

In Ex Post Facto studies, experimenters can control who belong to the treatment groups

A

False

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28
Q

Why do quasi designs have low internal validity?

A
  • No control over variables and antecedent conditions
  • Difficult to establish which preexisting conditions caused the results
  • Subject to the complex conditions in real life
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29
Q

This is a design where intact groups are studied and often they are differing in number

A

Non-equivalent Groups Design

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30
Q

How can the internal validity of a non-equivalent groups design be increased?

A

Make treatment groups as equal as possible

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31
Q

This design measures the same participants throughout time and studies how they change and develop

A

Longitudinal Design

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32
Q

This study measures different subject groups who are ate different stages in life

A

Cross-sectional Studies

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33
Q

This is a measurement of behavior before and after a treatment/intervention

A

Pretest/Posttest Design

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34
Q

This a 4-group design that aims to track changes with different application of pretest/treatment/posttest

A

Solomon 4-group Design

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35
Q

This is a statement about a predicted relationship between at least 2 variables

A

Hypothesis

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36
Q

What is the difference between a null and alternative hypothesis?

A

A null hypothesis is a prediction that an effect will not occur, while an alternative hypothesis states that an effect will be present

37
Q

Why is there a need for null hypotheses?

A

Since we cannot prove an experimental hypothesis using statistics, we can reject the null one instead to support the experimental hypothesis

38
Q

What is the difference between a directional and non-directional hypothesis?

A

Directional states that an effect will occur with the direction of that effect, while non-directional states that an effect will occur without specifying the direction

39
Q

What is the difference between a synthetic and non-synthetic statement?

A

Synthetic statement is one that can be true or false, while a non-synthetic one is always true or always false, or contradictory

40
Q

Aside from synthetic statements, what are the other characteristics of experimental hypotheses?

A
  • Testable
  • Falsifiable
  • Parsimonious
  • Fruitful
  • Positive
41
Q

In the hypothesis “If a, then b” , what are a and b?

A

Propositional variables

42
Q

This approach to forming a hypotheses is when reasoning is based on specific cases to general principles

A

Inductive Model

43
Q

This approach to forming a hypothesis is when reasoning is from theory to predict specific data or instances

A

Deductive Model

44
Q

These variables are the antecedent conditions that we intentionally manipulate in experiments

A

Independent Variable (DV)

45
Q

True or False: there only needs to be 1 level/form of IV in an experiment

A

False, there needs to be at least 2 levels

46
Q

What are the types of IVs?

A
  • Environmental (colors, music, temperature)
  • Task IVs
  • Psychological States
  • Set of Instructions
  • Psychological Interventions
47
Q

These variables are the ones expected to change because of the experimental treatment

A

Dependent Variable (DV)

48
Q

What are some methods of measuring the DV?

A
  • Accuracy
  • Reaction Time
  • Duration
  • Frequency
  • Intensity
  • Presence/Absence
  • Type of response
49
Q

This variable definition is precise and specific, including procedures and measurement

A

Operational Definition

50
Q

This variable definition is the commonly accepted one, based on theories or existing literature

A

Conceptual Definition

51
Q

This kind of operational definition describes exactly the specific behaviors recorded and how they were scored

A

Measured Operational Definition

52
Q

This kind of operational definition described the steps that were followed to set up the value of the IV

A

Experimental Operational Definition

53
Q

This is an aspect of reliability that emphasizes the similarity of results when measurement procedures are applied in more than one experiment

A

Consistency and Dependability

54
Q

This aspect of reliability emphasizes the consistency of ratings/scores from different observers

A

Interrater Reliability

55
Q

This aspect of reliability emphasizes the consistency of the scores of the same participant taken at different times

A

Test-Retest Reliability

56
Q

This aspect of reliability refers to the extent to which different parts of the questionnaire, test or other instrument assesses the same variable with consistent results

A

Interitem Reliability

57
Q

This is an aspect of validity that refers to how evident the variable that is being measured is from the instrument

A

Face Validity

58
Q

This is an aspect of validity that refers to how accurately test items represent the components of the construct being studied

A

Content Validity

59
Q

This is an aspect of validity that refers to how accurately the test predicts the behavior we are trying to measure

A

Predictive Validity

60
Q

This is an aspect of validity that refers to how scores on the measuring instrument correlates with another known standard for the variable being studied

A

Concurrent Validity

61
Q

This is an aspect of validity that refers to how well the operational definition of the variables matches the conceptual definition

A

Construct Validity

62
Q

These are variables other than the IV or DV that can influence results if not controlled

A

Extraneous Variables

63
Q

This is a threat to internal validity where external events may influence participants’ scores in one treatment differently than in another treatment

A

History Threat

64
Q

This is a threat to internal validity where internal changes (physical or psychological) in participants that occur during the study might affect their scores

A

Maturation Threat

65
Q

This is a threat to internal validity where participants become familiar with the measure and remember responses in subsequent testing

A

Testing Effects

66
Q

This is a threat to internal validity which is due to changes in the measurement instrument or measuring procedure

A

Instrumentation Threat

67
Q

This is a threat to internal validity where participants selected on the basis of extreme scores on one measurement tend to be less extreme on a second measurement

A

Statistical Regression Threat

68
Q

This is a threat to internal validity that occurs when subjects were not randomly assigned to the different conditions of an experiment

A

Selection Threat

69
Q

This is a threat to internal validity where participants drop out during an experiment due to different reasons

A

Subject Mortality Threat

70
Q

This is an extraneous variable that affects the environment of the testing conditions and need to be controlled

A

Physical Variables

71
Q

This is a technique in controlling physical variables where it is completely removed

A

Elimination

72
Q

This is a technique in controlling physical variables where they are set to be the same in all treatment conditions

A

Constancy of Conditions

73
Q

This is a technique in controlling physical variables where the effects are distributed across different treatment conditions

A

Balancing

74
Q

A type of extraneous variable that comes from the interaction between participants and experimenters that can affect results

A

Social Variables

75
Q

This phenomenon is when participants behave in a way they believe is expected of them

A

The “good subject” phenomenon

76
Q

This is a false explanation to disguise the actual research hypothesis to control demand characteristics

A

Cover Stories

77
Q

This is an aspect of extraneous social variables where the experimenter’s expectations affect their role in the experiment

A

Experimenter Bias

78
Q

How can experimenter bias be controlled?

A
  • Remain consistent with the standardized procedure
  • Minimal contact between experimenter and participant
79
Q

This is a method to control experimenter bias where neither the participants and experimenters know which treatment condition the participant is receiving

A

Double Blind Experiment

80
Q

This is an extraneous variable that comes from the different personal characteristics of experimenters and volunteer subjects

A

Personality Variables

81
Q

This is an extraneous variable that comes from the experimental procedure created within the experimental setting

A

Context Variables

82
Q

This is a type of design where subjects are randomly placed in each of 2 treatment conditions by random

A

Two independent-groups design

82
Q

A type of two independent groups design where there is one group with a treatment condition and the other without

A

Experimental-Control Groups Design

83
Q

A type of two independent groups design where two groups are exposed to two different values or levels of the IV

A

Two-Experimental-Groups Design

84
Q

This is a type of design where there are 2 treatment conditions and subjects are matched based on a subject variable thought to be highly related to the DV

A

Two matched-group design

85
Q

A type of design where there are more than 2 groups of subject and each group is run through different treatment conditions

A

Multiple groups design

86
Q

A method of assigning subjects where a table is used in an unbiased way

A

Random Number Table

87
Q

A method of assigning subjects where treatment blocks are created to assign the treatment

A

Block Randomization

Psychology (15 decks)

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