Question

In: Statistics and Probability

We counted the number of people who entered our store across the span of a week...


We counted the number of people who entered our store across the span of a week in the morning, afternoon, and evening. What is the simplest test to see if there is any difference in the frequency of people coming to our store at different times across days?

Group of answer choices

chi-square test of independence


two-way factorial ANOVA


independent t-test


one-way ANOVA with blocking


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Question 2

3 pts

We have three price points and three product colors and we have randomly assigned combinations of price points and colors to focus groups who have rated them on how likely they would be to purchase them. What is the simplest test we could use to see if there is any impact of price point, color, or the interaction?

Group of answer choices

chi-square test of independence


two-way factorial ANOVA


independent t-test


one-way ANOVA with blocking


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Question 3

3 pts

You have been conducting an experiment with 3 conditions and have done testing over the period of a week. What is the simplest test to use to see if there is an impact of the condition?

Group of answer choices

two-way factorial ANOVA


independent t-test


one-way ANOVA with blocking)


paired t-test


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Question 4

3 pts

We try to determine if we can use major, economic status, and age to predict an individual's marital status (single, married), which test should we use?

Group of answer choices

ANCOVA


Multiple regression


RANOVA


logistic regression


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Question 5

3 pts

We try to determine if we can use major, economic status, and age to see if an individual's purchase ability differs in terms of their economic status, which test should we use?

Group of answer choices

ANCOVA


logistic regression


Multiple regression


RANOVA


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Question 6

3 pts

We try to determine if we can use economic status and age to predict an individual's salary, which test should we use?

Group of answer choices

ANCOVA


RANOVA


logistic regression


Multiple regression


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Question 7

3 pts

We try to determine if we can use economic status and age to see if an individual's salary changes in a different period, which test should we use?

Group of answer choices

logistic regression


ANCOVA


Multiple regression


RANOVA


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Question 8

3 pts

In terms of different quasi-experimental designs, which one is the least reliable?

Group of answer choices

One-Group Posttest-Only Design


One-Group Pretest-Posttest Design


Nonequivalent Control Group Design


Time-Series Design


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Question 9

3 pts

What is the main purpose of EFA?

Group of answer choices

Find out the relationship between variables.


Catch the idea of the latent variables


Testing the internal validity of a cluster of variables.


Generate large factor loadings


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Question 10

3 pts

When performing CFA, which of the following statement is not correct?

Group of answer choices

We need a theory/previous study to support our model


Use goodness-of-fit to test the model


We try to establish a good model


Use rotations to improve factor loadings


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Question 11

10 pts

Please explain the assumption of sphericity? What's the consequence if we violate the assumption?

Solutions

Expert Solution

1.

2.

IF the colours are c1,c2,c3 and the prices are p1,p2,p3 then the table would look like

c1 c2 c3
p1
p2
p3

since there are two factors(price & colors) the answer shall be two-way factorial ANOVA

3. The question is not clear . However , there is a single factor (condition) and since there is more than 1 levels(3 conditions) , one-way ANOVA with blocking is likely to be the answer.

4. The outcome variable is a dichotomous variable(2 categories:- married/single) . with categorical(major, economic status,) & continuous (age) variables. In such scenarios logistic regression is best for prediction/classification.

5. Assuming purchase ability is a categorical variable , and economic status is also continuous the most appropriate answer would be Logistic regression.

6.economic status = continuous variable(explanatory ) & salary = continuous (predicted variable) ,the most appropriate answer would be Multiple  regression.


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