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Final Exam

Total questions: 109

Worksheet time: 1hrs 3mins

Name
Class
Date
1.

Which of the following example research questions can be used for a Chi Square goodness of fit test?

a)

There are bags of candy with five flavors of candy in each bag. The bags should contain an equal number of pieces of each flavor. Are the proportions of the five flavors in each bag the same?

b)


We want children with a lot of experience, some experience, and no experience shared evenly across the team. Suppose we know that 20 percent of the players in the league have a lot of experience, 65% have some experience and 15 percent are new players with no experience. Do these percentages match desired proportions?


c)

You are studying mental health conditions. Does the proportion of your sample who report have various mental health conditions match those of the general population?

2.

What is the Chi square test of independence?

a)

Checks whether different variables are likely to be related or not.

b)

Determines whether different a categorical variable follows a hypothesized distribution.

c)

Determines if the variables are multicollinear.

d)

Determines if the variables need to be transformed.

3.

What is a Chi square goodness of fit test?

a)

Determines whether a categorical variable follows a hypothesized distribution.

b)

Checks whether different variables are likely to be related or not.

c)

Examines if the mean scores of two groups are significantly different.

d)


Controls for Type 1 error by reducing the p level.

4.

Which of the following adjust for inflated type 1 error (false positive)?

a)

Bonferroni

b)

Holm

c)

Tukey

d)

Scheffe

e)

Aikake

5.

Which of the following is the correct procedure when sphericity is violated?

a)

Follow the lowest epsilon

b)

When epsilon is less than 0.75, use Greenhouse Geisser

c)

When epsilon is more than 0.75, use Huynd Feldt

d)

Follow the highest epsilon

6.

What is the non-parametric equivalent of a repeated measures ANOVA?

a)

Friedman test

b)

Mauchly’s test

c)

Bonferroni test

d)

Kruskall Wallis

7.

What does the VIF (Variance Inflation Factor) do?

a)

Detects multicollinearity when there’s a correlation between predictors (IVs)

b)

Estimates how much the variance is inflated due to multicollinearity of the model.

c)

1 = not correlated; between 1 and 5 moderately correlated; greater than 5 highly correlated

d)

Determines if the variable scores fit the model

8.

When would you use a standardized regression coefficient (B)?

a)

When variables are on fundamentally different scales.

b)

When you don't get statistical significance with unstandardized coefficients

c)

Never

d)

When you need to run a power analysis after checking for effect size.

9.

What are the assumptions of a linear regression?

a)

Homogeneity of variance

b)

Independence of observations

c)

No multicollinearity (need uncorrelated predictors)

d)

Normality

e)

Linearity between predictor and residuals

10.

What does a balanced cell design mean in Factorial ANOVA?

a)

The sample size of all possible combinations of conditions is equal.

b)

The sample size of all possible combinations is large.

c)

The ANOVA cells are appropriate given the IV labels.

d)

The main effects are equal.

11.

How many main effects do you have for a 2 x 2 factorial ANOVA?

a)

2

b)

4

c)

8

d)

1

12.

What is bootstrapping used for?

a)

To resample from the collected data to re-estimate parameters and effects

b)

To develop better research approaches

c)

To form a normal distribution when assumptions are violated

d)

To ensure that power is maximized

13.

What is another term for an outside influence that can affect the outcome or explain a relationship?

a)

Confound

b)

Outlier

c)

3rd variable

14.

What can you do when homogeneity of variance is violated in a one-way between groups ANOVA?

a)

Conduct a Welch one-way test

b)

Conduct a Kruskal-Walls Test

c)

Conduct a Freidman test

d)

Use a Yates test

15.

The following central tendency scores for exam scores are below.  How would you describe this distribution and the type of effect?

mean: 78

median: 90

mode: 99

a)

Negative skew, ceiling effect

b)

Negative skew, floor effect

c)

Positive skew, ceiling effect

d)

Positive skew, floor effect

16.

The number of standard deviations a score is above or below the mean is indicated by a(n) __________.

a)

Z score

b)

raw score

c)

outlier

d)

interval

17.

A study indicates that in general the more fruit students eat before a test, the better they do on the test. However, beyond a certain point, the more fruit students eat, the worse they do on the test. Thus, the relation between amount of fruit eaten and test performance is an example of 

a)

a positive linear correlation.

b)

a curvilinear correlation.

c)

a negative linear correlation.

d)

no correlation.

18.

When do we use a Yate’s correction in a Chi Square test?

a)

When the degree of freedom is 1

b)

When the expected frequency is 5 or less

c)

When there are repeated observations

d)

When we use continuous variables as IVs

19.

What are the assumptions of a Repeated Measures ANOVA?

a)

No outliers

b)

Normality

c)

Linearity

d)

Sphericity

20.

Which of the following estimates are used for evaluation when there is a violation of sphericity?

a)

Greenhouse-Geisser

b)

Cox Test

c)

Huynd Feldt

d)

Bartlett test

21.

What does sphericity mean?

a)

Equal variances among the differences between all possible pairs of within-subject conditions (level of the IV)

b)

Equal variances among the differences between all possible pairs of between-subject conditions (between IVs)

c)

Linearity of scores between 2 group means

d)

Normality between 2 group means

22.

What is true of linear regression?

a)

Forecasts an effect

b)

Identifies the strength of a relationship between a predictor and a response variable.

c)

How much the dependent variable changes with a change in one or more independent variables.

d)

Determines the strength (weight) of predictors

23.

What term is used when the difference between predicted and observed scores is large?

a)

outlier

b)

leverage

c)

influence

d)

extreme

24.

Which of the following can be tested using a logistic regression?

a)

Do body weight, calorie intake, fat intake and age have an influence on heart attacks? (Yes v. No)

b)

What is the strength of the relationship between dose (low, medium, high) and effect (mild, moderate, and severe)?

c)

What type of drink (coffee, soft drink, tea and water) is preferred based on location in U.S. and Age?

d)

Do several measures of personality differentiate those who pursue different majors in college?

25.

Which of the following statement(s) are true about ANOVA?

a)

ANOVA tests group differences

b)

ANOVA and regression rely on SS and F tests

c)

ANOVA computes correlations and predictions.

d)


ANOVA is used when the DV is categorical.

26.

What is eta in a factorial ANOVA?

a)

Sum of squares for the effect over the total sum of squares (represents the proportion of variance in the outcome that can be explained by the effect of the factor of interest).

b)

Sum of squares for the effect over the sum of squares of the effect. Does include variance accounted by the other factors in the model.

c)

The sum of squares divided by the degrees of freedom.

d)

The sum of all p levels that would inflate Type 1 error.

27.

What can you do when a between-subjects ANOVA violates the assumption of normality?

a)

Conduct a Welch one-way test

b)

Conduct a Kruskal-Walls Test

c)

Conduct a Freidman test

d)

Use a Yates test

28.

If a study finds that the scarier the movie a person is watching, the more popcorn the person will eat, the relationship between scariness and popcorn is an example of a(n) __________ correlation.

a)

positive linear

b)

negative linear

c)

curvilinear

d)

no correlation

29.

With Sign: N = 4; df = 3; M = 79; S2 = 18.67

No Sign:   N = 4; df = 3; M = 85; S2 = 12.00

dftotal = 6; S2pooled = [(3/6)(18.67)] + [(3/6)(12)] = 9.34 + 6 = 15.34

S2M1 = S2M2 = 15.34/4 = 3.84

S2difference = 3.84 + 3.84 = 7.68; Sdifference = 2.77

t needed (df = 6, p < .05, one-tailed) = –1.943

t = (79 – 85) / 2.77 = –2.17

What is the correct statistical notation for the results?

a)

t(6) = -2.17, p < 5%

b)

t(6) = -2.17, p > 5%

c)

t(6) = -1.943, p < 5%

d)

t(6) = -1.943, p > 5%

30.

Contingency tables in Chi Square tests

a)

Show number of observations in groups or combinations of groups.

b)

Are used to estimate the critical value of a given statistic.

c)

Used to determine statistical power in a T test.

d)

Estimates Type 1 error in an ANOVA.

31.

Which of the following example research questions can be used for a Chi Square test of independence?

a)

A veterinary clinic records a list of dog breeds they see as patients. The 2nd variable is whether owners feed dry food, canned food, or a mixture. Can the clinic order food based only on the total number of dogs, without consideration of their breeds?

b)

Does the proportion of ethnicity in Las Vegas match the proportions in New York City?

c)

Does watching violent tv shows relate to religious affiliations (Catholic, Protestant, etc.)

d)

Is there a relation between mentorship experiences and ethnicity?

32.

What is another name for a repeated measures ANOVA with one factor (IV)?

a)

One way within subjects ANOVA

b)

One way between subjects ANOVA

c)

Mixed design ANOVA

d)

Random effects ANOVA

33.

Which of the following statements are true for a linear regression?

a)

The effect size of a simple regression (R2) is equivalent to the squared correlation (r2) when dealing with one predictor and one response variable.

b)

The effect size of a simple regression is equivalent to the squared t value of the predictors.

c)

The effect size of a simple regression is equivalent to the estimated residuals.

d)

The t statistic of each of the predictors sums to the effect size

34.

To test homogeneity of variance in a linear regression

a)

Run a Kolmogorov–Smirnov test

b)

Create a histogram

c)

Plot fitted values against standard residuals (want a straight horizontal line)

d)

Run a non-constant variance test. If p > .05, there is no relationship, and therefore homogeneity of variance.

35.

Which of the following will improve (R squared) in regression by chance?

a)

More predictors

b)

More dependent variables

c)

Less dependent variables

d)

More residuals

36.

What does variance of scores within a treatment group indicate?

a)

Spread of scores

b)

Consistency of measurement

c)

Reliability

d)

Width of the distribution

37.

Select all options that can test for normality of distributions.

a)

QQ plot

b)

Krukall Wallis Test

c)

Kurtosis, Skew

d)

Histogram

e)

Welch test

38.

When figuring out the range of scores in 95% of the population, the cut off point on the z score number line is

a)

+1.96, -1.96

b)

+1.96

c)

-1.96

d)

+2.5, -2.5

39.

The Fisher’s test is used in Chi Square when

a)

expected frequency is 5 or less

b)

expected frequency is more than 5

c)

there are repeated observations

d)

we use continuous variables as IVs

40.

How do you increase power in Chi Square tests?

a)

Use simple contingency tables (less categories) and large sample sizes.

b)

Use complex contingency tables (more categories) and small sample sizes.

c)

Use repeated measures

d)

Use linear approximations

41.

How do we test for the degree for sphericity?

a)

Epsilon

b)

Mu

c)

Sigma

d)

Eta

42.

R squared in a linear of regression is also called the

a)

Criterion of determination

b)

Coefficient of determination

c)

Proportion of variance in the outcome variable that can be accounted for by the predictors

d)

Regression error

43.

Which of the following is true about F in a regression analysis:

a)

Is equal to the variance not explained by the model.

b)

Is equal to the variance explained by the extra parameters (predictors) divided by the variation not explained by the extra parameters.

c)

Determines the indirect effects of the predictors

d)

Indicates a mismatch between observed and expected proportions.

44.

In the regression line equation:  y = b0 + b1x1

a)

The predictor coefficient is b1

b)

The score of the predictor is x

c)

Y is the predicted score

d)

b1 is the intercept

45.

What is partial eta in a factorial ANOVA?

a)

Sum of squares for the effect over the sum of squares of the effect and residuals as opposed to total variance.

b)

Sum of squares for the effect over the total sum of squares (represents the proportion of variance in the outcome that can be explained by the effect of the factor of interest).

c)

The sum of squares divided by the degrees of freedom.

d)

The sum of all p levels that would inflate Type 1 error.

46.

What kind of Factorial ANOVA is this? A study looking at the effect of gender and athlete type on mental health scores. 

a)

Between group factorial ANOVA

b)

Within group factorial ANOVA

c)

Mixed factorial ANOVA

d)

Combined Factorial ANOVA

47.

If a research article presented the results of an analysis of variance as, "F (5, 64) = 3.60, p < .05," then how many groups were there in the study?

a)

7

b)

6

c)

64

d)

63

48.

In which of the following situations would a t test for independent means be conducted?

a)

a comparison of the SAT scores of a group of 10 students who completed a special SAT preparation course compared to the scores of students in general on the SAT

b)

a comparison of scores of participants in a memory study where one group is assigned
to learn the words in alphabetical order and another group is assigned
to learn the words in order of length of the word

c)

a comparison of participants' scores on a skills test before and after attending a training session intended to improve the skill

d)

a comparison of participants' logical reasoning skills with the general population 

49.

Which of the following about epsilon is true?

a)

The lower the number, the greater the violation.

b)

If the epsilons are different, choose the higher number (more conservative)

c)

F statistics does not change

d)

Greenhouse-Geisser and Huynd-Felt corrects the degrees of freedom for the F distribution

e)

Multiply epsilon by the degrees of freedom numerator (k-1) and the degrees of freedom denominator (k-1) (n-1).

50.

What kind of Factorial ANOVA?  A study comparing the altruism scores of different class grades (freshmen, sophomore, junior, and senior) before and after watching a documentary about poverty.

a)

Between groups

b)

Within groups

c)

Mixed factorial ANOVA

d)

Factorial ANCOVA

51.

Tukey HSD (Honestly Significant Difference) in Factorial ANOVA

a)

Examines all relevant pairwise comparisons between groups

b)

Constructs confidence intervals for all comparisons

c)

Calculates adjusted p value for any specific comparison

d)

Is a post hoc test

52.

Which of the following is an ideal ANOVA F ratio in an analysis?

a)

1

b)

0

c)

100

d)

-100

53.

Joe conducts an analysis of variance. If he rejected the null hypothesis, the most likely F value is

a)

0.64

b)

1.01

c)

3.57

d)

–5.12

54.

What is the symbol for z score cross products?

a)

ZxZy

b)

xy

c)

Zxy

d)

ZY

55.

Interaction effect between degree attained and major studied on income. Which statement(s) are true?

a)

The effect of degree on income depends on major studied

b)

The effect of major studied on degree depends on income

c)

The effect of major studied on income depends on degree

d)

The effect of degree on major depends on income

56.

How many interaction effects are there in a 3x2 factorial ANOVA

a)

3

b)

1

c)

2

d)

24

57.

What is the intercept in a linear regression?

a)

The effect size

b)

Error

c)

The number of units predicted variables increases after adding predictors

d)

The mean of the predicted variable (y), if the other IVs are set to zero

58.

If homogeneity of variance is violated in a regression analysis, you can

a)

Use heteroscedasticity correlated covariance matrix (sandwich estimators)

b)

Run a Holm test to check equivalence of p values

c)

Bootstrap to find out if it is still violated

d)

Use a Bartlett test to test against the median

59.

How do you deal with multicollinearity in a regression analysis?

a)

Take a composite of the IVs that are correlated

b)

Check if interaction between the IV and its log is significant

c)

Drop the IV(s) that are correlated

d)

Divide the original p level by the number of possible comparisons

60.

In an ANOVA with a between-groups population variance of 30 and a within-groups estimate of 25, the F ratio is

a)

30/25 = 1.20

b)

(30-25)/30 = 0.17

c)

25/(30-25) = 5.00

d)

25/30 = 0.83

61.

The coefficient of determination (r^2) is .72 between temperature (x) and ice cream sales (y). Which statement is true?

a)

Effect of type of ice cream on sales depends on temperature 72% of the time

b)

72% of changes in temperature depends on how much people pay for ice cream

c)

72% of the variance in sales of ice cream can be explained by temperature

d)

72% of ice cream is affected by temperature

62.

The probability of making a Type 1 error is ____

a)

equal to 1 - beta

b)

equal to beta

c)

equal to the critical value level (p level)

d)

never known

63.

Which of the following is the largest effect size?

a)

-.90

b)

+.80

c)

+.50

d)

-.30

64.

Estimated population variances for each group are 12.8, 16.3, 15.1, and 19.9. Estimated within group population variance

a)

(12.82 + 16.32 + 15.12 + 19.92)/ (4-1) = 351.18

b)

(12.82 + 16.32 + 15.12 + 19.92)/ 4 = 263.39

c)

(12.8 + 16.3 + 15.1 + 19.9) / (4-1) = 21.37

d)

(12.8 + 16.3 + 15.1 + 19.9)/4 =16.03

65.

How would you describe this distribution and the type of effect? Mean: 78, Median: 60, Mode: 56.

a)

Negative skew, ceiling effect

b)

Negative skew, floor effect

c)

Positive skew, ceiling effect

d)

Positive skew, floor effect

66.

How would you describe this distribution and the type of effect? Mean: 78, Median: 78, Mode: 78

a)

Positive skew, ceiling effect

b)

Negative skew, ceiling effect

c)

Negative skew, floor effect

d)

Normal

67.

What is the definition of a main effect?

a)

Compares only 2 specific cells

b)

difference between
two groups (conditions) in one
grouping variable (IV)

c)

pattern of
differences across one row will not
be the same of patterns of
differences across another row

d)

effect of one IV within one
level of the second IV

68.

What type of effect is this?

a)

Main effect contrasts

b)

Simple effects (simple main effects)

c)

Interaction effect

d)

Simple contrasts

69.

What type of effect is this?

a)

Main effect contrasts

b)

Simple effects (simple main effects)

c)

Interaction effect

d)

Simple contrasts

70.

What kind of effect is this?

a)

Main effect contrasts

b)

Interaction effect

c)

Simple effects (simple main effects)

d)

Main effect

71.

What type of contrast is this?

a)

Main effects contrast

b)

Interaction effect

c)

Simple effects (simple main effects)

d)

Simple contrasts

72.

What type analysis is this? Are there differences in stress scores (ratio) across 3 different occupations and 2 different cities?

a)

factorial ANOVA: between group design

b)

factorial ANOVA: mixed design

c)

factorial ANOVA: within group design

d)

ANOVA

73.

What kind of analysis is this? Are there differences in stress scores (ratio) across 3 different occupations and 2 times points (early. mid career)?

a)

factorial ANOVA: between group design

b)

factorial ANOVA: mixed design

c)

factorial ANOVA: within group design

d)

ANOVA

74.

How many IVs in a 2 x 2 x 3 x 5 Factorial ANOVA?

a)

5

b)

4

c)

60

d)

None of the above

75.

What is true of a repeated measures design?

a)

Error variance is smaller

b)

Reduces individual differences not associated to conditions

c)

Participants serve as their own control, more power, lower sample size needed

d)

Error variance is higher

76.

Variance of the paired differences between conditions (e.g., time) is the same for all comparison levels of a factor

a)

Normality

b)

Homogeneity of variance

c)

Linearity

d)

Sphericity

77.

If Mauchly's test is violated, the F ratio becomes inflated

a)

True

b)

False

78.

Which choices are true about epsilon?

a)

epsilon is 1, sphericity is met

b)

epsilon is <1, sphericity is not met

c)

epsilon is >1, sphericity is not met

d)

none of the above

79.

Which of the following is the least conservative estimate of epsilon?

a)

Lower bound

b)

Wilcoxon estimate

c)

Huynh-Feldt estimate

d)

Greenhouse-Geisser estimate

80.

Which of the following is the most conservative estimate of epsilon, which is typically not used?

a)

Lower bound

b)

Wilcoxon estimate

c)

Huynh-Feldt estimate

d)

Greenhouse-Geisser estimate

81.

When should you use Greenhouse-Geisser?

a)

If GGe < .75

b)

If GGe > .75

c)

When GGe is 0

d)

None of the above

82.

When sphericity is violated, the new degrees of freedom is (k = groups, n = # of scores)

a)

df(num) = k - 1; df(error) = (k - 1)(n - 1)

b)

df(num) = k + 1; df(error) = (k + 1)(n + 1)

c)

df(num) = epsilon(k - 1); df(error) = epsilon(k - 1)(n - 1)

d)

None of the above

83.

Which of the following are post hoc tests?

a)

Scheffe

b)

Tukey

c)

Holm

d)

Wilcoxon signed rank test

84.

Kendall's W

a)

effect size for chi square

b)

effect size for Friedman's test

c)

effect size for dependent t test

d)

effect size for repeated measures ANOVA

85.

What type of analysis would you use?

1 DV (nominal w/ multiple categories), 1+ IV(s) (continuous, normally distributed)

a)

Dichotomous logistic regression

b)

Ordinal logistic regression

c)

Multinominal logistic regression

d)

Linear discriminant analysis

86.

1 DV (nominal, multiple categories), 1+ IV(s) (nominal, ordinal, continuous; no assumptions about data)

a)

Dichotomous logistic regression

b)

Ordinal logistic regression

c)

Multinomial logistic regression

d)

Linear discriminant analysis

87.

When is degrees of freedom 1 in a Chi Square test?

a)

In a 1x1 design

b)

When there is one IV being analyzed in a goodness of fit test

c)

In a 2x2 design

d)

Never

88.

What best describes a Brown-Forsythe test in an ANOVA?

a)

determines the absolute deviation from the outcome variable and the mean

b)

determines the deviation from the outcome variable and the mean

c)

determines the absolute deviation from the outcome variable and the median

d)

determines the deviation from the outcome variable and the median

89.

What is the null hypothesis of the Levene's test?

a)

Spread of scores is identical for all groups

b)

The scores follow a normal distribution

c)

The spread of scores is equal to 0 for all groups

d)

The slope of the regression line is 0

90.

What is the difference between an ANOVA and a Kruskal Wallis test?

a)

An ANOVA compares group standard deviations; whereas Kruskal Wallis compares group means

b)

An ANOVA uses Bonferroni for post hoc comparisons; whereas Kruskal Wallis cannot apply post hoc tests

c)

An ANOVA compares group means; whereas Kruskal Wallis compares rank totals

d)

An ANOVA compares within group variance; whereas Kruskal Wallis compares between group variance

91.

Multiple R squared

a)

Will decrease when you add more predictors

b)

Proportion of variance in outcome variable explained by the regression

c)

Influences sphericity

d)

Reflects the proportions in chi square analysis

92.

Which of the following is an ideal Kruskal Wallis H for an analysis?

a)

1

b)

100

c)

0

d)

-100

93.

Which of the following is the most popular post hoc test following a significant Kruskal-Wallis test?

a)

Nemenyi test

b)

Dunn's test

94.

Leverage helps identify

a)

the "extreme" H values

b)

the "extreme" mean values

c)

"extreme" predictor x values

d)

"extreme" predicted y values

95.

You have 4 different age groups you need to compare: 5yrs, 10yrs, 15yrs, 20yrs. If you want to compare pre-teens & younger with the older groups, what would be the contrasts?

a)

-1, 0, 0, +1

b)

0, +1, -1, 0

c)

-1, -1, +1, +1

d)

0, 0, +1, -1

96.

Click all statements that may apply

a)

main effect for age

b)

main effect for expectations

c)

Interaction effects between years and expectations on IQ test

d)

main effect for IQ

97.

Select all statements that may apply

a)

Interaction effect between age and expectations on IQ scores

b)

main effect for age

c)

main effect for expectations

d)

main effect for IQ scores

98.

Education administrators are trying to determine if the performance on 5 different achievement tests (numerical/continuous) can predict the program that high schoolers select: general, academic, vo/tech)

a)

chi square

b)

factorial ANOVA

c)

logistic regression

d)

repeated measures ANOVA

99.

What is true about Type 1 error?

a)

equal to p

b)

equal to alpha

c)

inflated due to violation of sphericity

d)

inflated due to multiple comparisons

100.

In a correlation analysis, the results were: t(50) = 2.776, p < .05

Which of the following statements is true?

a)

sample size is 52

b)

the results are not statistically significant

c)

sample size is 50

d)

the correlation coefficient is 2.776

101.

What is a correlation coefficient?

a)

sum of squares of ZxZy

b)

the sum of ZxZy

c)

the mean of the sum of squares of ZxZy

d)

the mean of ZxZy

102.

What is the red area called?

a)

power

b)

type 1 error

c)

type 2 error

d)

McNemar test

103.

Do the proportion of participants who felt safe (yes or no) differ when before wearing a cycling helmet as opposed after putting the cycling helmet on?

a)

Factorial ANOVA

b)

McNemar test

c)

Chi Square Goodness of Fit

d)

Chi Square Test of Independence

104.

If you are choosing to run an independent t-test, and normality is not met, what test would you run?

a)

Wilcoxon's Rank Sum Test (Mann Whitney U)

b)

Mauchly's test

c)

Levene's test

105.

If you're choosing to run a paired-samples t-test and it violates the normality assumption, what test would you run?

a)

Wilcoxon Signed Rank Sum test

b)

Wald's test

c)

Welch's t test

d)

Wilcoxon Paired Signed Rank test

106.

When do you run a Welch's test?

a)

Levene's test, p < .05

b)

Shapiro Wilk's, p < .05

c)

Levene' test, p > .05

d)

Kruskall Wallis, p > .05

107.

What is SS/df?

a)

estimated variance of a distribution of scores

b)

estimated standard deviation of a distribution of scores

c)

standard deviation of mean scores

d)

variance of mean scores

108.

Shapiro Wilk's test is better than QQ plot when sample size is less than 50.

a)

True

b)

False

109.

What is the effect size for Chi Square?

a)

Epsilon

b)

Cramer's V

c)

Cohen's d

d)

Eta Squared