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Count data regression

Authored by Mohammad AL-jabri

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Professional Development

Used 1+ times

Count data regression
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8 questions

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1.

MULTIPLE CHOICE QUESTION

20 sec • 1 pt

1. What is the primary purpose of count data regression?

A) To analyze categorical data

B) To build models for count data

C) To compare mean differences

D) To test for normality

2.

MULTIPLE CHOICE QUESTION

20 sec • 1 pt

2. Which of the following is a key assumption of Poisson regression?

A) The variance is greater than the mean

B) The mean and variance are equal

C) The data follows a normal distribution

D) The residuals are independent and identically distributed

3.

MULTIPLE CHOICE QUESTION

20 sec • 1 pt

3. If the variance is greater than the mean in Poisson regression, what issue arises?

A) Heteroscedasticity

B) Overdispersion

C) Multicollinearity

D) Endogeneity

4.

MULTIPLE CHOICE QUESTION

20 sec • 1 pt

4. Which method is commonly used to correct for overdispersion in Poisson regression?

A) Linear regression

B) Logistic regression

C) Negative Binomial regression

D) Probit regression

5.

MULTIPLE CHOICE QUESTION

20 sec • 1 pt

5. What is the primary difference between Poisson regression and Negative Binomial regression?

A) Poisson regression assumes overdispersion, while Negative Binomial does not

B) Poisson regression assumes mean and variance are equal, while Negative Binomial allows variance to be greater than the mean

C) Negative Binomial regression is only used for binary data

D) Poisson regression is non-parametric

6.

MULTIPLE CHOICE QUESTION

20 sec • 1 pt

6. In Poisson regression, which method is used to check assumptions?

A) Checking residual plots

B) Examining the mean and standard deviation of the variable of interest

C) Performing a t-test

D) Using ANOVA

7.

MULTIPLE CHOICE QUESTION

20 sec • 1 pt

7. What should the ratio of deviance to degrees of freedom be in a properly fitted Poisson regression model?

A) Close to 0

B) Close to 1

C) Greater than 2

D) Exactly equal to the sample size

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