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Statistics Quiz

Total questions: 40

Worksheet time: 20mins

Name
Class
Date
1.

Which of the following best describes a factorial design?

a)

A study with more than one factor

b)

A study with only one factor

c)

A study with repeated measures

d)

A study with only dependent variables

2.

In a two-factor ANOVA, how many hypothesis tests are conducted?

a)

One

b)

Three

c)

Four

d)

Two

3.

What does a main effect represent in a two-factor ANOVA?

a)

The correlation between factors

b)

The effect of one factor averaged across levels of the other factor

c)

The combined effect of both factors

d)

The error variance

4.

What indicates an interaction in a two-factor ANOVA graph?

a)

No variance

b)

Parallel lines

c)

Non-parallel lines

d)

Equal means

5.

Which formula represents the F-ratio?

a)

Mean differences / Sample size

b)

Sum of squares total / Degrees of freedom

c)

Variance between treatments / Variance expected by chance

d)

Eta squared / Variance

6.

What is the purpose of adding a second factor in ANOVA?

a)

To increase variance

b)

To avoid hypothesis testing

c)

To reduce variance caused by individual differences

d)

To eliminate main effects

7.

Which assumption is NOT required for two-factor ANOVA?

a)

Normality of populations

b)

Equal sample sizes

c)

Independence of observations

d)

Equal variances

8.

What is eta squared (η²) used for?

a)

Computing correlation

b)

Testing normality

c)

Calculating degrees of freedom

d)

Measuring effect size

9.

Which of the following is true about correlation?

a)

It measures the relationship between two variables

b)

It measures causation

c)

It measures regression slope

d)

It measures variance explained by ANOVA

10.

A positive correlation means:

a)

No relationship exists

b)

As X increases, Y increases

c)

The slope is negative

d)

As X increases, Y decreases

11.

The null hypothesis in correlation states:

a)

ρ ≠ 0

b)

ρ = 0

c)

ρ > 0

d)

ρ < 0

12.

Degrees of freedom for Pearson correlation are:

a)

n - 1

b)

n - 3

c)

n

d)

n - 2

13.

Which correlation is used for ordinal data?

a)

Phi-coefficient

b)

Point-biserial

c)

Pearson

d)

Spearman

14.

The coefficient of determination (r²) indicates:

a)

Slope of regression line

b)

Strength of correlation

c)

Percentage of variance explained

d)

Error variance

15.

Which correlation is used when one variable is dichotomous?

a)

Spearman

b)

Point-biserial

c)

Pearson

d)

Phi-coefficient

16.

Which correlation is used when both variables are dichotomous?

a)

Phi-coefficient

b)

Spearman

c)

Pearson

d)

Point-biserial

17.

Regression is used to:

a)

Compute chi-square

b)

Predict values of Y from X

c)

Test independence

d)

Measure variance

18.

In the regression equation Ŷ = bX + a, what does b represent?

a)

Slope

b)

Error

c)

Intercept

d)

Variance

19.

In the regression equation Ŷ = bX + a, what does a represent?

a)

Slope

b)

Intercept

c)

Variance

d)

Error

20.

Which of the following is NOT a use of regression?

a)

Predicting Y from X

b)

Measuring correlation strength

c)

Estimating slope and intercept

d)

Testing independence of categorical variables

21.

The regression constant “a” is also called:

a)

Slope

b)

Intercept

c)

Variance

d)

Error

22.

The least-squares regression line minimizes which of the following?

a)

Variance between treatments

b)

Sum of squared errors between predicted and actual Y

c)

Correlation coefficient

d)

Chi-square statistic

23.

The standard error of estimate measures:

a)

Strength of correlation

b)

Average distance between predicted and actual Y values

c)

Variance explained by regression

d)

Degrees of freedom

24.

In regression, the slope (b) can also be computed using:

a)

Eta squared

b)

Pearson correlation and standard deviations

c)

Chi-square formula

d)

ANOVA F-ratio

25.

Multiple regression allows:

a)

Testing independence of categorical variables

b)

Using several predictors to improve accuracy

c)

Eliminating variance completely

d)

Measuring only one variable

26.

In multiple regression, the equation is:

a)

Ŷ = bX + a

b)

Ŷ = b1X1 + b2X2 + a

c)

F = MSbetween/MSwithin

d)

r = Σ(ZxZy)/N

27.

The symbol R² in regression indicates:

a)

Percentage of variance explained by regression

b)

Correlation coefficient

c)

Error variance

d)

Degrees of freedom

28.

Which test is nonparametric?

a)

t-test

b)

ANOVA

c)

Chi-square

d)

Regression

29.

Parametric tests require:

a)

Frequency counts

b)

Interval or ratio data

c)

Ordinal data only

d)

Dichotomous variables

30.

The chi-square test for goodness of fit evaluates:

a)

Mean differences

b)

Proportions in categories

c)

Regression slopes

d)

Correlation strength

31.

Observed frequency (fo) refers to:

a)

Expected counts from hypothesis

b)

Actual counts from sample data

c)

Variance explained by regression

32.

How is the expected frequency (fe) calculated?

a)

fe = pn

b)

fe = ΣX²/n

c)

fe = r² × SSY

d)

fe = MSbetween/MSwithin

33.

Which of the following is the correct formula for the chi-square statistic?

a)

F = MSbetween/MSwithin

b)

χ² = Σ((fo - fe)² / fe)

c)

r = SP/(SSX·SSY)

d)

Ŷ = bX + a

34.

What is the formula for degrees of freedom for chi-square goodness of fit?

a)

n - 1

b)

C - 1

c)

n - 2

d)

(R - 1)(C - 1)

35.

How do you calculate the degrees of freedom for chi-square independence?

a)

n - 1

b)

C - 1

c)

(R - 1)(C - 1)

d)

n - 2

36.

When is the phi-coefficient used?

a)

Both variables are dichotomous

b)

One variable is ordinal

c)

One variable is dichotomous, one continuous

d)

Both variables are continuous

37.

Cramer's V is used when:

a)

Both variables are continuous

b)

Matrix larger than 2×2

c)

One variable is ordinal

d)

Regression with two predictors

38.

A chi-square test should not be used when:

a)

Expected frequency < 5 in any cell

b)

Sample size is large

c)

Variables are categorical

d)

Observed frequencies are integers

39.

Which of the following is true about nonparametric tests?

a)

They require interval data

b)

They are distribution-free

c)

They always use regression

d)

They cannot test independence

40.

The chi-square test for independence evaluates:

a)

Whether two categorical variables are related

b)

Whether regression slope is significant

c)

Whether correlation is zero

d)

Whether means differ across treatments