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final Flashcards

1
Q

-Different participants are observed onetime in each group or at each level of a factor

A

between-subjects design

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2
Q

Levels of a between-subjectsfactor are manipulated, then different participants are randomlyassigned to each group or to each level of that factor and observedone time

A

between-subjects experimental design

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3
Q

Type of factor in which different participants areobserved in each group or at each level of the factor

A

between subjects factor

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4
Q

A statistical procedure used to test hypotheses concerning thedifference between two population means, where the variance in oneor both populations is unknown.
* Making comparisons between two independent groups

A

two independent sample t test

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5
Q

refers to the selection of participants such that different participants areobserved one time in each sample or group

A

independent samples

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6
Q

categorical variable (school) with two levels(Towson and JMU)

A

IV

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7
Q

continuous variable (IQ)

A

DV

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8
Q

The inferential statistic you use to look at ___between groups is the independentsamples t-test

A

mean differences

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9
Q

assume data in each population are normally distributed

A

normality

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10
Q

assume that the data were obtained using a randomsampling procedure

A

random sampling

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11
Q

each measured outcome is independent; one outcome isnot influenced by any other

A

independence

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12
Q

assume variance in each population is equal to each other. This is satisfied when larger variance is not greater than two times that of the smaller

A

equal variances (homogeneity of variances)

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13
Q

how to determine homogeneity v hetero. of variance?

A

levene’s test

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14
Q

if we reject null, SPSS reports t-test that does not assume…

A

equal variance

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15
Q

The null states that there is no difference and the alternative states that the difference is different than ___

A

0

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16
Q

Remember that we will only really report an effect size IF we ___

A

reject the null

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17
Q

place the difference between two sample means in the numerator and the pooled sample standard deviation in the denominator

A

estimated cohen’s d

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18
Q

results of t-test

A
  • The value for the test statistic
  • Degrees of freedom
  • p value
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19
Q

Cohen’s d is most often reported with ___tests

A

t

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20
Q

participants in each group or sampleare related

A

related or dependent sample

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21
Q

they are observed in more than one group

A

repeated measures

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22
Q

They are matched, experimentally or naturally, based on the common characteristics or traits that they share

A

matched pairs design

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23
Q

repeated measures design

A
  • A research design in which the same participants are observed in each sample.
  • This is the most common related samples design
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24
Q

type of repeated measures design in which researchers measure a dependent variable for participants before (pre) and following(post) some treatment

A

pre-post design

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25
Q

type of repeated measures design where researchersobserve the same participants across many treatments but not necessarilybefore and after a treatment

A

within-subjects design

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26
Q

Matching through ___ is typical for experiments in which the researcher manipulates the traits or characteristics used to match theparticipants

A

experimental manipulation

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27
Q

Matching through __ is typical for quasi-experiments in which participants are matched based on their preexisting traits or characteristics

A

natural occurrence

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28
Q

a statistical procedure used to test hypotheses concerning two related samples selected from populations in which the variance in one or both populations is unknown
* Comparing mean difference between pairs of scores in population to those observed in a sample

A

related samples t test

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29
Q

score or value obtained by subtracting two scores. In a related samples t test, this is obtained prior to computing the test statistic

A

difference score

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30
Q

the larger the value, the ___ likely a sample mean difference could occur if the null hypothesis were true

A

less

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31
Q

The degrees of freedom for the related-samples t test

A

n-1

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32
Q

we assume thatdifference scores were obtained from different individualswithin each group or treatment

A

independence w/in groups

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33
Q

An estimate of the proportion of variance in a dependent variablethat can be explained by a treatment

A

proportion of variance

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34
Q

in hypothesis testing, we are often interested in ___ than two groups

A

more

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35
Q

is a statistical procedure used to test hypotheses for one or more factors concerning the variance among two or more group means, where the variance in one or more populations is unknown

A

An Analysis of Variance (ANOVA), also called the F test

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36
Q

one factor tested

A

one way anova

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37
Q

two factors tested

A

two way anova

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38
Q

research design in which we select independent samples,meaning that different participants are observed at each level of a factor

A

between-subjects design

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39
Q

of groups

A

k

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40
Q

of participants per group

A

n

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41
Q

of total participants in study

A

N

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42
Q

any variation that can be measured in a study. In the one-waybetween-subjects ANOVA, there are two sources of variation

A

source of variation

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43
Q

variance of group means

A

between groups variation

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44
Q

variation attributed to error

A

within groups (error) variation

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45
Q

the distribution of possible outcomes for the test statistic is ___ skewed

A

positively

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46
Q

The distribution, called the F distribution, is derived from a sampling distribution of F ___

A

ratios

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47
Q

The variances measured in an ANOVA test are computed as ___ squares, or variance

A

mean

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48
Q

It is computed as mean square (or variance) betweengroups divided by the mean square (or variance) withingroups

A

F statistic

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49
Q

variance between groups/variance within groups

A

F obtained

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50
Q

As M1, M2, M3 deviatefrom one another (getfurther apart), their variance will ___

A

increase

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51
Q

As variances within-conditions ___, discrepancy of the means is less meaningful

A

increases

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52
Q

As variances within-conditions ___, discrepancy of the means is more meaningful

A

decrease

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53
Q

statistical procedure computed following a significant ANOVA todetermine which pair or pairs of group means significantly differ

A

post hoc test

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54
Q

These tests are necessary when k > 2 because multiple comparisons are needed

A

post hoc

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55
Q

All post hoc tests control for experimentwise ___

A

alpha

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56
Q

Bonferonni is far too ___

A

conservative

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57
Q

Tukey’s HSD is most -__

A

conservative

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58
Q

Fisher’s LSD is most ___

A

liberal

59
Q

a statistical procedure used to test hypotheses for one factor with two or more levels concerning the variance among group means. This test is used when the same participants are observed at each level of a factor and the variance in any one population is unknown

A

one-way within-subjects ANOVA

60
Q

An ANOVA determines whether ___significantly vary in the population

A

group means

61
Q

estimates how much of the variability in the dependent variable can be accounted for by the levels of the factor

A

proportion of variance

62
Q

The within-subjects design is associated with ___ power to detect aneffect than the between-subjects design because some of the error in thedenominator of the test statistic is removed

A

more

63
Q

The power of the one-way within-subjects ANOVA is largely based upon the assumption that observing the same participants across groups will result in more ___ responding, or changes in the dependent variable, between groups

A

consistent

64
Q

statistical technique that describes the linear relationship between two variables.

A

correlation

65
Q

Variables are usually observed in ___ environment, with no manipulation by the researcher;

A

natural

66
Q

however, correlation methods can be applied to ___ data as well

A

experimental

67
Q

statistical procedure used to describe the strength and direction of thelinear relationship between two factors

A

correlation

68
Q

In a correlation, we treat each factor like a ___ variable and measure the relationship between the pair.

A

dependent

69
Q

In behavioral research, we mostly describe the ___ (or straight line) relationshipbetween two factors

A

linear

70
Q

Correlations are typically illustrated through a ___ plot

A

scatter

71
Q

used to measure the strength and direction of the linear relationship, or correlation, between two factors (-1 to +1)

A

correlation coefficient

72
Q

Values closer to ___ indicate stronger correlations

A

±1.0

73
Q

indicates only the direction or slope of the correlation

A

the sign of the correlation coefficient

74
Q

the values of the two variables move in the same direction

A

positive correlation

75
Q

the values of the two variables move in the opposite direction

A

negative correlation

76
Q

reflects how consistently scores for each factor change

A

strength of correlation

77
Q

When plotted in a graph, scores are more consistent the closer they fall to a ___ line

A

regression

78
Q

means there is no linear pattern between two factors

A

zero correlation

79
Q

occurs when each data point falls exactly on a straight line

A

perfect correlation

80
Q

-the best fitting straight line to a set of data points. A best fitting line is the line that minimizes the distance of all data points that fall from i

A

regression line

81
Q

linear vs. non-linear

A

form

82
Q

Slopes that “flatten out” at the top are common in the social sciences

A

monotonic

83
Q

used to measure the direction and strength of the linear relationship of two factors in which the data for both factors are measured on an interval or ratio scale of measurement

A

pearson correlation coefficient

84
Q

The value in the ___ reflects the extent to which values on the x-axis (X) and y-axis (Y) vary together

A

numerator

85
Q

the extent to which the values of two factors vary together

A

covariance

86
Q

The extent to which values of X and Y vary independently, or separately, is placed in the ___

A

denominator

87
Q

correlations

A

describe the degree of linear relationship between 2 variables
* Does not explain why the variable are related
* Does NOT indicate cause and effect relationship

88
Q

is just an index, not a measurement scale

A

correlation coefficient

89
Q

A correlation can be used as a ___ statistic

A

descriptive and inferential

90
Q

mathematically equivalent to eta-squared, and is used to measure the proportion of variance of one factor (Y) that can be explained by known values of a second factor (X)

A

coefficient of determination

91
Q

01 = small; .09 medium; .25 large

A

r^2

92
Q

assumption that there is an equal (“homo”)variance or scatter(“scedasticity”) of datapoints dispersed along the regression line

A

Homoscedasticity

93
Q

assumption that the best way to describe a pattern of data is using a straight line

A

linearity

94
Q

is a problem that arises when the direction of causality between two factors can be in either direction

A

reverse causality

95
Q

or third variable, is an unanticipated variable that could be causing changes in one or more measured variables

A

confounding variable

96
Q

Outliers can obscure the relationship between two factors by altering the ___of an observed correlation

A

direction and strength

97
Q

A problem that arises when the range of data fo rone or both correlated factors in a sample is limited or restricted, compared to the range of data in the population from which the sample was selected

A

restriction of range

98
Q

All correlation coefficients are derived from the ___ correlation

A

pearson

99
Q

To summarize correlations, report the ___for each correlation coefficient

A

strength, direction, and p value

100
Q

means that additional factors do not enter into or confound the XY relationship

A

nonspuriousness

101
Q

SS regression + SS residual

A

total variance

102
Q

or known variable (X)–the variable with values that are known and can be used to predict values of another variable

A

predictor variable

103
Q

or to-be-predicted variable (Y)–the variable with unknown values that can be predicted or estimated, given known values of the predictor variable

A

criterion variable

104
Q

linear relationship between two variables (x and y)can be described by the equation y = a + b(x) + e

A

linear equation

105
Q

This parameter that we estimate tells us the value of y when x equals 0

A

y-intercept

106
Q

The ___(formed by the equation y = a + b(x)) is the one line that best describes theset of data

A

regression line or line of best fit

107
Q

SS(xy)/SS(x)

A

slope

108
Q

statistical procedure used to test hypotheses for one or more predictor variables to determine whether the regression equation for a sample of data points can be used to predict values of the criterion variable (Y) given values of predictor variable (X) in the population

A

analysis of regression, or regression analysis

109
Q

variance that is related to changes in X

A

regression variation

110
Q

Variance that is not related to changes in X

A

residual variation

111
Q

Analysis of regression measures only variance in ____, because that is what we want to predict

A

Y

112
Q

an estimate of the standard deviation or distance that a set of data points falls from the regression line. The standard error of estimate equals the square root of the mean square residua

A

standard error of estimate

113
Q

the regression line allows us to make predictions but it doesn’t provide information about the ___ of the predictions

A

accuracy

114
Q

Provides a measure of the typical distance between a regression line (predicted scores) and the actual data points

A

standard error of estimate

115
Q

As the correlation increases (gets closer to 1.00 or -1.00), the data points are more tightly clustered around the regression line, and thus we will have better prediction (___ prediction error)

A

less

116
Q

As the correlation gets smaller (approaches 0), the data points arespread further out from the regression line, and thus we will haveworse prediction (____ prediction error)

A

greater

117
Q

parameter estimate based on the sample will not, on average, equal true value of regression coefficient in population

A

bias

118
Q

statistical method that includes two or more predictor variables in the equation of a regression line to predict changes in a criterion variable

A

multiple regression

119
Q

One advantage of including multiple predictors in the regression equation is that we can detect the extent to which two or more ___ variables interact

A

predictor

120
Q

A family of statistical procedures that do not rely on the assumptions of parametric tests. In particular, they do not assume that the sampling distribution is normally distributed

A

nonparametric tests

121
Q

statistical procedure used to test hypotheses about the discrepancy between the observed and expected frequencies for the levels of a single categorical variable or two categorical variables observed together

A

chi square test

122
Q

Indicates how well a set of observed frequencies fits with what was expected

A

chi square

123
Q

The null hypothesis for the chi-square goodness-of-fit test is that the expected frequencies are ____

A

correct

124
Q

The alternative hypothesis is that the expected frequencies are ____

A

not correct

125
Q

The larger the discrepancy between the observed and expected frequencies, the more likely we are to ___ the null hypothesis (chi square)

A

reject

126
Q

positively skewed distribution of chi-square test statistic values for all possible samples when the null hypothesis is true

A

chi square distribution

127
Q

The df for each chi-square distribution are equal to the number of levels ofthe categorical variable (k) minus 1: df =____

A

k - 1

128
Q

Because the chi-square distributionis positively skewed, the rejectionregion is always placed in the ___ tail

A

upper

129
Q

(1) is not interpreted in terms of differences between categories* (2) can be used to confirm that a null hypothesis is correct

A

chi square test

130
Q

(chi) We compare the discrepancy between observed and expected frequencies at each level of the ____ variable, thereby making a total of k comparisons.
* Do not compare across ___ of the categorical variable

A

categorical; levels

131
Q

(chi) Because the test statistic does not compare differences between the discrepancies, there is no statistical basis for identifying which discrepancies are actually ___

A

significant

132
Q

When a chi-square goodness-of-fit test is significant,we mostly speculate as to which ___ frequencies were significantly different from the expected frequencies.

A

observed

133
Q

The chi-square goodness-of-fit test is one of the few hypothesis tests used to confirm that a null hypothesis is ____

A

correct

134
Q

Decision to ___ the null is the goal of the chi-square goodness-of-fit test
.* It is a rare example of a test used for this purpose.

A

retain

135
Q

A key assumption for the chi-square goodness-of-fit test is that the observed frequencie sare recorded ____

A

independently

136
Q

(chi) One restriction using this test is that the size of an expected frequency should never be smaller than ____ in a given category

A

5

137
Q

statistical procedure used to determine whether frequencies observed at the combination of levels of two categorical variables are similar to frequencies expected

A

chi square test for independence

138
Q

The chi-square test for independence is interpreted similar to a ____

A

correlation

139
Q

If two categorical variables are ____, they are not related or correlated

A

independent

140
Q

If two categorical variables are ____, they are related or correlated

A

dependent

141
Q

The phi correlation coefficient can be used in place of a _____ chi-squaretest for independence

A

2x2

142
Q

The _____coefficient and the chi-square test statistic are related in that we can use the value of one to compute the other

A

phi correlation

143
Q

measures of effect size for chi-square of independence

A
  • Phi coefficient
  • Cramer’s V
144
Q

To summarize the chi-square tests for independence, also report the ____

A

effect size

hth 354 (1 decks)

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