Research Flashcards

1
Q

IV

A

independent variable or experimental variable

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2
Q

DV

A

dependent variable

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3
Q

what happens with the IV in an experiment

A

the IV gets manipulated by the researcher

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4
Q

what happens with the IV in an experiment

A

Manipulated by the researcher

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5
Q

Examples of an independent variable

A

counseling, exercise, mindfulness

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6
Q

Examples of an dependent variable

A

weight, IQ, drinks, time, money spent,

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7
Q

quasi-experimental

A

research that does not use random sampling

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8
Q

systematic sampling/kth sampling

A

1st participant is randomly sampled, then the next is picked every 10th person

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9
Q

non-probablity sample

A

subjects are selected by the researcher

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10
Q

convenience sampling

A

the intact existing group is used with no random sampling

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11
Q

quota sample

A

your sample has the same type of characteristics that existing in population being studied

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12
Q

hypothesis

A

hunch/idea

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13
Q

RA fisher

A

father of statistics and experimental design

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14
Q

each experiment has what two hypothesis

A

null hypothesis, experimental hypothesis

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15
Q

null hypothesis

A

no difference/significance between the control and experimental groups

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16
Q

test of significance

A

a statistical test that assesses whether a result obtained from an experiment is important enough or not

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17
Q

level of sigificance

A

confidence level of research
probability of difference between groups alpha level

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18
Q

social sciences significance

A

p or probabilty is less than .05

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19
Q

if p is <.05

A

probability that differences are less than 5% chance

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20
Q

the lower the p (.01 or .001) the?

A

the chance factors or the more convincing the experiment

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21
Q

greater statistical power, the more?

A

confidence in the validity of the research

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22
Q

two types of resarch errors

A

Type I and Type II

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23
Q

Type I error

A

reject null when true
false positive

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24
Q

Type II Error

A

accept null when false
false negative

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25
Q

the probability of making a type I error is

A

equal to the level of significance

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26
Q

If your p value is .05 then?

A

.05 is the probablity of making a type I error

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27
Q

If your p value is less than .05

A

accept null hypothesis

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28
Q

extraneous variables are

A

errors

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29
Q

internal validity

A

makes the conclusions of a causal relationship credible and trustworthy

High internal validity demonstrates causal link

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30
Q

external validity

A

can the expreimental findings be generalized to other people/groups

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31
Q

instrumentation threat

A

threat to validity in the instrumentation or measurment methods

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32
Q

maturation

A

threat to validity effect of time rather than IV on text subject results

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33
Q

statistical regression

A

low scores move up and high scores move down toward the mean

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34
Q

external threat to validity

A

findings will not generalize to real world

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35
Q

t-test/student’s t-test

A

tests a hypothesis between two normally distrubuted samples and must have 30 participants

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36
Q

correlated t-test

A

same group measured on 2 occasions (pre/post test)

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37
Q

What does an Anova do

A

compares more than 2 groups / analysis of variance

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38
Q

results of Anova is what

A

F value

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39
Q

more than one DV requires

A

MANOVA

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40
Q

what is an ANCOVA

A

analysis of covariance/an adjustment to the groups

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41
Q

hawthorn effect/reactive effect

A

an individual being observed does better when being observed

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42
Q

correlational research asks

A

does a relationship between an IV and DV exist

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43
Q

Pearson product-moment correlation/correlation coefficient

A

correlation of choice in a counseling study

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44
Q

range of a correlation coefficient

A

-1.00 to 0 to +1.00

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45
Q

correlation coefficient

A

a statistical relationship between two variables

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46
Q

what is a perfect correlation

A

-1 or +1

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47
Q

what is a negative or inverse correlation

A

one variable goes up when another goes down

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48
Q

what is a zero correlation

A

0.00
no relationship

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49
Q

gaussian curve is also a

A

bell shaped curve and is normally distributed

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50
Q

measures of central tendancy

A

mean, median, mode

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51
Q

mean

A

average or most useful measure

52
Q

median

A

middle or 50th percentile

53
Q

mode

A

most often occuring amount/top or high point of graph

54
Q

in a normal distrbution the mean, median and mode are what

A

the same value

55
Q

a curve with 2 points

A

bimodal curve

56
Q

multimodal curve

A

two modes

57
Q

distrbution tail to right

A

positively skewed

58
Q

distribution tail to left

A

negatively skewed

59
Q

y-axis

A

ordinate - goes up and down like the letter y

60
Q

x-axis

A

absissa

61
Q

histogram

A

bar graph

62
Q

range

A

measure of variablity or difference between the highest and lowest

63
Q

SD or Standard deviation is

A

the square root of the variance

64
Q

95%

A

number of scores/cases that fall between 2 +/- standard diviations

65
Q

99.70%

A

number of scores/cases that fall between 3 +/- standard diviations

66
Q

z-score

A

standard deviation

67
Q

t-score

A

mean is 50 and score is 10 points above or below the mean

68
Q

stanines

A

standard 9 scores and divide the distrbution into 9 equal intervals hwere the mean is 5 with a standard diviation of 2

69
Q

descriptive statistics include:

A

range,
variance,
standard deviation
not experimental

70
Q

nominal scale

A

Independent of each other - identify and classify, are qualitiative - eye color, blood type

71
Q

ordinal scale

A

describe variables that are rank ordered - high med low

72
Q

interval scale

A

describe numbers that are scaled at equal distances - Fahrenheit

73
Q

ratio scale

A

each number is measured from zero - height, weight

74
Q

survey

A

questionnaire to a sample population

75
Q

ethnographic research

A

holistic and inductive , overall dynamics

76
Q

inductive reasoning

A

genernalize based on specific observations

77
Q

deductive reasoning

A

general principles inform a hypothesis

78
Q

halo effect

A

Thorndyke - rate on one characteristic but really influenced by another

79
Q

horn effect

A

a attribute you find negative will influcence your decision

80
Q

rosenthal effect

A

experiement expectations might influence change

81
Q

double blind

A

both the researcher and the groups do not know who is in what group

82
Q

norms

A

normal, typical average person who to is being studied

83
Q

N

A

number of subjects in a study

84
Q

N=1

A

single subject design - case study

85
Q

AB design

A

A = baseline meansurement, B=apply intervention then see if something changed

86
Q

ABC design

A

two treatment interventions

87
Q

ABA design

A

when a treatment returns to baseline measurement

88
Q

ABAB design

A

Baseline, treatment, baseline, treatment, ending on a treatment phase

89
Q

counterbalancing

A

the way stimulus is presented can bias a study. Counterbalancing changes the way interventions are presented to groups

90
Q

percentile rank

A

percentage is different than percentile: percentage is scoring 50% of test questions, pecentile is scoring better than 50% of test takers

91
Q

raw score

A

unaltered scores

92
Q

metaanaylsis

A

combine multiple research studies

93
Q

parametric

A

interval/ratio

Fall on a continuum

t-test, anova, chi-square test

94
Q

nonparametric

A

nominal or ordinal

do not lie on a continuum

Mann Whitney U test, Kruskal Wallis test, Wilcoxon’s signed ranks test

95
Q

Empirical rule in a normal distribution:

A

All scores will fall within 3 standard deviations from the mean as 68% at 1 SD, 95% at 2 SD, and 99% 3 SD

96
Q

standard error of measurement

A

how much measured test scores are spread around a “true” score
directly related to a test’s reliability

97
Q

the smaller the sample size

A

the greater increase of error or decrease in reliability

98
Q

interrater reliability

A

the extent to which independent evaluators produce similar ratings in judging the same abilities or characteristics in the same target person or object

99
Q

correlation coefficient

A

measures the linear correlation between two sets of data

100
Q

Pearson product-moment correlation coefficient

A

parametric test to measure the linear relationship between two normally distributed variables

101
Q

Random error

A

Chance errors
mainly affects precision

102
Q

systematic error

A

Consistent or proportional difference between observable and true values

affects the accuracy of a measurement

103
Q

types of systematic error

A

Response bias
social desirability bias
Experimenter drift

104
Q

Kurtosis

A
105
Q

Stratified Random Sampling

A

Helps you pick a sample that reflects the groups in your participant population(e.g., matching census percentages)

106
Q

Cluster Sampling

A

Selecting subgroups without randomly selecting individuals within those groups. E.g., randomly selecting classrooms

107
Q

Purposeful Sampling

A

Selecting people based on who is likely most knowledgeable about the topic, or because they represent needed characteristics. Example: selecting CEOs for a qualitative study about the impact of power on personality

108
Q

directional hypothesis

A

does the IV increase the DV

109
Q

non-directional hypothesis

A

How does the IV affect the DV
does it increase or decrease?

110
Q

t-test

A

test between 2 groups

111
Q

Chi square ( χ 2 ) tests

A

used when t-tests cannot be performed because the data do
not resemble a normal distribution

112
Q

Mann Whitney U test

A

non-parametric test between 2 groups
t-test equivariant

113
Q

Kolmogorov Smirnov Z procedure

A

test between 2 groups for less than 25 participants
Used instead of the Mann-Whitney

114
Q

Kruskal Wallis test

A

Used instead of the Mann Whitney when there are more than two IV groups

Equivalent to anova

115
Q

Wilcoxon’s signed ranks test

A

Paired group tests
Nonparametric equivalent to dependent t-test for one group only (pre and post-test)

116
Q

Friedman’s rank test:

A

Used instead of the Wilcoxon for paired group tests of more than two groups

117
Q

Analysis of
variance (ANOVA)

A

used instead of a t-test for multiple groups

118
Q

Analysis of
covariance (ANCOVA)

A

Testing two groups and controlling for a possible confounding variable

119
Q

Multiple analysis of covariance
(MANCOVA)

A

Similar to ANCOVA but with multiple dependent variables

120
Q

Between group t-tests =

A

“independent,” “unpaired”
(e.g., CBT vs. placebo)

121
Q

Within group t-tests =

A

“dependent,” “paired”
(e.g., pre and post-test)

122
Q

Coefficient of Determination

A

To determine the amount of shared variance between two variables
(i.e., effect size), we square

123
Q

The Factorial ANOVA statistical test is used to determine:

A

if two or more sets of groups are significantly different from each other on your variable of interest. Your variable of interest should be continuous, be normally distributed, and have a similar spread across your groups. In addition, you should have enough data (more than 5 values in each group).

124
Q

Dependent t-test

A

paired t-test
Compare means of 2 groups

125
Q

Spearman’s rank correlation coefficient

A

nonparametric test that measures the strength and direction of association between two ranked variables.
equivalent to Pearson’s coefficient