Brainscape's Knowledge GenomeTM

Browse over 1 million classes created by top students, professors, publishers, and experts.


See full index

GRAD Research & Design > Final Exam > Flashcards

Final Exam Flashcards

1
Q

What is association?

A

There must first be a relationship or an association between the IV and the DV

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Between-subjects design:

A

Each set of scores is obtained from different groups of participants

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Within-subjects design:

A

Different sets of scores are obtained from the same group of participants

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

Characteristics of between-subjects design:

A
  • Experimental research wherein a researcher manipulates an IV ► then measures the DV for each participant
  • Goal: determine whether differences exist between two or more treatment conditions
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

Disadvantage of between-subjects design:

A
  • large # of participants

- scores from each person is unique & may produce high variability in scores

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

What are the 2 major sources of confounding variables in between-subjects?

A
  1. confounding from ind. differences (assign. bias)

2. confounding from env. variables

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

What is a confounding variable?

A

any extraneous variable systematically differentiating the groups (ex: age)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

What are the 3 techniques to limit confounding variables?

A
  1. random assignment
  2. matching groups
  3. holding variables constant
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

Large differences between treatments are good because…

A

they provide evidence of differential treatment effects

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

Large differences within treatments are bad because…

A

differences that exist inside the treatment conditions determine the variance of the scores (large variance can hide patterns in the data)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

What is a factor?

A

The independent (or quasi-independent) variable that designates the groups being compared

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

What are levels?

A

Individual conditions or values that make up a factor

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

What is a factorial design?

A

A study that combines two or more factors

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

Alt Hypothesis H1:

A

There is at least one mean difference among the populations

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

Is between-treatments variance the numerator or denominator of the F-ratio?

A

numerator

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

Is within-treatments variance the numerator or denominator for the f-ratio?

A

denominator

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

F ratio formula:

A

differences including any treatment effects/differences with no treatment effects

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

If the null hypothesis is true….

A

then the value of F will be close to 1.00

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

What are the assumptions of a ANOVA?

A
  • The observations within each sample must be independent.
  • The population from which the samples are selected must be normal.
  • The populations from which the samples are selected must have equal variances(homogeneity of variance).
  • Violating the assumption of homogeneity of variance risks invalid test results.
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
20
Q

What is a partial correlation?

A

A partial correlation measures the relationship between two variables while mathematically controlling the influence of a third variable by holding it constant

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
21
Q

Pearson’s correlation uses:

A

data from interval or ratio measurement scales

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
22
Q

Spearman (Rs) uses:

A

ranking (ordinal scale)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
23
Q

Point-biserial correlation:

A

One variable has only two values(called a dichotomous or binomial variable)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
24
Q

R2 (squared):

A
  • measure of effect size

- amount of variance accounted for

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
25
Q

Phi coefficient:

A
  • Both variables are re-coded to values 0 and 1 (or any two digits)
  • Both variables (X and Y) are dichotomous
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
26
Q

Regression analysis

A

precisely defines the line.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
27
Q

General equation for a line:

A

Y = bX + a

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
28
Q

Regression:

A

a line that is the best fit for the actual data that minimizes prediction errors.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
29
Q

What is latin squared?

A

a way to counterbalance

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
30
Q

Beta coefficients in multiple linear regression

A

The higher the beta value the greater the impact of the predictor variable on the criterion variable

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
31
Q

Mediator variables:

A

A mediation model is one that seeks to identify and explain the mechanism or process that underlies an observed relationship between a predictor variable and the criterion variable via the inclusion of the third hypothetical variable, that is, a mediator variable.
ex: iq –> study habits –> exam scores

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
32
Q

Moderator variables:

A

Amoderator variable is a thirdvariablethat affects the strength of the relationship between a predictor variableand a criterion variable in regression analysis

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
33
Q

Parametric tests share several assumptions:

A
  • Normal distribution in the population
  • Homogeneity of variance in the population
  • Numerical score for each individual
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
34
Q

Nonparametric tests are needed if…

A

if research situation does not meet all these assumptions.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
35
Q

For Chi-square &nonparametric tests:

A

do not state hypothesis in terms of a population parameter

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
36
Q

Categorizing makes what?

A

nonparametric

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
37
Q

Choice of statistical procedure determined primarily by the…

A

the level of measurement.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
38
Q

What is attrition?

A

People who drop out of the study

39
Q

What is external validity?

A

The extent to which the results of a research study can be generalized

40
Q

What is a threat to external validity?

A

Any characteristic of a study that limits the ability to generalize the study’s results

41
Q

What are the 3 kinds of generalization, which can involve threats to validity?

A
  • Generalization from a sample to the general population
  • Generalization from one research study to another
  • Generalization from a research study to a real-world situation
42
Q

In a quasi experiment you don’t have…

A

control or manipulation

43
Q

What are threats to internal validity in a quasi experiment?

A
  • Retesting & Instrumentation
  • Attrition
  • History
  • Maturation
  • Regression toward the mean
44
Q

Is effect size effected by increasing sample size?

A

NO

45
Q

What is external validity?

A

extent to which the results of a research design can be GENERALIZED

46
Q

What is ecological validity?

A

extent to which the research is conducted in situations that are similar to the everyday life experiences

47
Q

What are field experiments?

A

experiments conducted in a natural environment (ex: library, school, anywhere other than a lab)

48
Q

When n is small (less than 30), the t distribution will be…

A

flatter & more spread out than the normal z distribution

49
Q

Does the t statistic require the population standard deviation?

A

no

50
Q

Does the z test require the population standard deviation?

A

yes

51
Q

Which combination of factors is most likely to produce a significant value for an independent-measures t statistic?

A

large mean difference & small variance

52
Q

For an independent-measures t statistic, the estimated standard error measures how much…

A

difference is reasonable to expect between the sample means if there is no treatment effect.

53
Q

For an independent measures research study, the value of cohen’s d or r squared describes what?

A

how much difference there is between the two treatments

54
Q

Increasing the variance, increases the denominator, decreases the _________.

A

t-statistic

55
Q

How does a repeated measures study reduce the variance?

A

by removing individual differences

56
Q

Does an ANOVA allow researchers to compare several treatments conditions w/o a hypothesis test?

A

Yes

57
Q

If the null hypothesis is true, the F-ratio for ANOVA is expected to be…

A

near 1.00

58
Q

When are post hoc tests needed?

A

when you reject H0 (indicating at least one main difference)

59
Q

What is a repeated-measures design also known as?

A

within-subjects design

60
Q

What is a repeated-measures design?

A
  • two separate scores are obtained for each individual in the sample
  • same subjects are used in both treatment conditions
61
Q

What are advantages of using a repeated-measures design?

A
  • Requires fewer subjects
  • Able to study changes over time
  • Reduces or eliminates influence of individual differences
  • Substantially less variability in scores
62
Q

What does ANOVA stand for?

A

analysis of variance

63
Q

What is an advantage of using a t-test?

A

can be used to compare more than two treatments at the same time

64
Q

What is the null hypothesis for the ANOVA?

A

the level or value on the factor does not affect the dependent variable

65
Q

What is the alt hypothesis (H1) for the ANOVA?

A

There is at least one mean difference among the populations

66
Q

What is the goal of a experimental research study?

A

To demonstrate a cause-and-effect relationship between two variables

67
Q

What are 3 techniques to control extraneous variables?

A
  1. Holding variables constant
  2. Matching values across treatment conditions
  3. Control by randomization
68
Q

What Is not guaranteed to be successful in balancing variables?

A

randomization

69
Q

What are manipulation checks?

A
  • Directly measure whether the IV had the intended effect on the participant
  • Ways to check the manipulation
70
Q

What is pilot testing?

A

Studies conducted before the research to determine if the manipulation is impactful

71
Q

What is the advantage of using ANOVA over a t-test?

A

can be used to compare MORE THAN TWO treatments at the same time

72
Q

Phi coefficient:

A

dichotomous

73
Q

Pearson:

A

interval & ratio

74
Q

Spearman:

A

ordinal

75
Q

What is a single-group design?

A
  • a group of individuals are measured AFTER they have had the experience of interest
  • cannot be used to draw conclusions about how an experience has affected individuals involved because there is no control group.
76
Q

What is a comparison-group design?

A
  • uses a comparison group that is expected to be similar but not equivalent to the experimental group
  • need to draw definitive conclusions
77
Q

What is a single-group before-after design?

A

(sometimes referred to as a pretest-posttest design) is a research study in which a series of observations is made over time for one group of participants

78
Q

What is a comparison-group before-after design?

A
  • (sometimes called pretest–posttest nonequivalent control group design) compares two non-equivalent groups
  • One group is measured twice ►once before a treatment is administered and once after
  • This design attempts to limit threats to internal validity
  • Two way ANOVA used
79
Q

What is a time series design?

A
  • has a series of observations for each participant before a treatment or event and a series of observations after the treatment or event
  • These are research designs with longitudinal research designs in which the dependent measure is assessed for one or more groups more than twice, at regular intervals, both before and after the experience of interest occurs.
80
Q

What are the assumptions of a parametric test?

A
  • normal distribution in the population
  • homogeneity of variance in the pop.
  • numerical score for each individual
81
Q

What is a nonparametric test?

A
  • they are needed if research situation does not meet all parametric assumptions
  • doesn’t state the hypothesis in terms of a specific population parameter
82
Q

What is regression?

A

a method of finding an equation describing the best fitting line for a set of data

83
Q

What does r represent?

A

measures the correlation size

84
Q

When to do a chi square test?

A

classification in non-numerical categories (ordinal or nominal)

85
Q

When to do a t-test?

A

for numerical scores (interval/ratio scale)

86
Q

When to use a pearson correlation?

A

for data having linear relationships (interval or ratio data)

87
Q

What is a partial correlation?

A

measure the relationship between 2 variables while mathematically-controlling the influence of a 3rd variable

88
Q

What is a correlation hypothesis test?

A

Sample correlation r used to test population ρ (rho)

89
Q

What is a mediator variable?

A

seeks to identify & explain the mechanism/process that underlies an observed relationship between a predictor variable & the criterion variable

90
Q

What is a moderator variable?

A

is a third variable that affects the strength of the relationship between a predictor variable & a criterion variable in regression analysis

91
Q

What is a mixed factorial design?

A

an ANOVA using both repeated & independent measures

92
Q

What are extraneous variables?

A

variables other than the IV that causes changes in the DV

93
Q

Regression towards the mean:

A

ex: when someone takes the test more than once they score closer to the mean

GRAD Research & Design (1 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2024 Bold Learning Solutions. Terms and Conditions