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1.Which assumption is not relevant to a mixed-factorial ANOVA? a. homogeneity of variances b. independence of scores for between-subjects measure c. sphericity for between-subjects measure

1.Which assumption is not relevant to a mixed-factorial ANOVA?

a. homogeneity of variances

b. independence of scores for between-subjects measure

c. sphericity for between-subjects measure

d. all of the above

e. none of the above

2. Which of the following is not a type of categorical variable?

a. Nominal

b. Binary

c. Interval

d. Ordinal

3.Which of the following is not an assumption of parametric tests?

a. Normality

b. Dependency

c. Homoscedasticity/homogeneity of variance

d. Linearity

4.Which of the following statements regarding covariance is not true?

a. A positive value indicates that as one variable deviates from the mean, the other variable does too.

b. A negative value indicates that the correlation will most likely be non-significant.

c. Covariance is dependent on the scale of measurement used, and can be compared across different variables.

d. The denominator in the equation for covariance isn-1.

e. Both b and c.

f. Both b, c and d.

5. Recent research has shown that women who skip breakfast are more likely to give birth to baby girls, whereas women who eat breakfast are more likely to have baby boys. To test this, we took a sample of pregnant women who already knew the gender of their baby and asked them how often they eat breakfast (every day, some days, or never). We want to analyse our data with a chi-square test. How would our analysis be described?

a. 1 2

b. 3 3

c. 3 2

d. 2 2

6.With 22 contingency tables (i.e., two categorical variables both with two categories) no expected values should be below ____.

a. 0.8

b. 10

c. 5

d. 1

7.A distribution that is leptokurtic is:

a. skewed to the left.

b. overly flattened.

c. overly pointed in the middle.

d. skewed to the right.

8.Standard deviations of 3.29 captures:

a. 90% of scores

b. 95% of scores

c. 99% of scores

d. 99.9% of scores

9.What are phi and Cramr'sVused for?

a. They can be used as remedies when the assumption of expected frequencies has been violated.

b. They are used as a correction when the assumption of independence has been violated.

c. They are measures of the strength of association between two continuous variables.

d. They are measures of the strength of association between two categorical variables.

10.How are the degrees of freedom calculated for a chi-square test?

a.(r-1) / (c-1)

b. (r-1)(c-1)

c.(r2)-(c2)

d. (r+ 1)-(c+ 1)

11.Which of the following statements about the chi-square test is false?

a. The chi-square test can be used to check how well a model fits the data.

b. The chi-square test is used to quantify the relationship between two categorical variables.

c. The chi-square test is based on the idea of comparing the frequencies you observe in certain categories to the frequencies you might expect to get in those categories by chance.

d. In some circumstances the chi-square test can be used on continuous variables.

12.A partial correlation:

a. Is another name for a semi-partial correlation

b. Examines the unique contribution of a variable (X1) in explaining the variance in a second variable (X3) while holding a third variable (X3) constant across all variables (both X1 and X2).

c. Examines the unique contribution of a variable (X1) in explaining the variance in a second variable (X2) while holding a third variable (X3) constant across either X1 or X2, but not both.

d. Both a and c.

13.Imagine you conducted a study to look at the association between whether an expectant mother eats breakfast (or not) and the gender of her baby. Cramr's V = .22. How would you interpret this value?

a. 2.2% of the variation in frequency counts of baby gender (boy or girl) can be explained by whether or not the mother ate breakfast every day.

b. There is a medium to large association between the gender of the baby and whether or not the mother ate breakfast every day.

c. There was a small to medium association between baby gender and whether the mother ate breakfast every day.

d. 22% of the variation in frequency counts of baby gender (boy or girl) can be explained by whether or not the mother ate breakfast every day.

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