This set of Data Science Multiple Choice Questions & Answers (MCQs) focuses on “Binary and Count Outcomes”.

1. How many components are present in generalized linear models ?

a) 2

b) 4

c) 6

d) None of the Mentioned

View Answer

Explanation: Generalized linear models involve three components.

2. Point out the wrong statement:

a) Additive response models don’t make much sense if the response is discrete, or strictly positive

b) Transformations are often easy to interpret in linear model

c) Regression models are used to predict one variable from one or more other variables

d) All of the Mentioned

View Answer

Explanation: Transformations are often hard to interpret in linear model.

3. Which of the following component is involved in generalized linear models ?

a) An exponential family model for the response

b) A systematic component via a linear predictor

c) A link function that connects the means of the response to the linear predictor

d) All of the Mentioned

View Answer

Explanation: GLM is a flexible generalization of ordinary linear regression that allows for response variables that have error distribution models other than a normal distribution.

4. Collection of exchangeable binary outcomes for the same covariate data are called _______ outcomes.

a) random

b) direct

c) binomial

d) none of the Mentioned

View Answer

Explanation: The multivariate regression model for binary outcomes gives odds ratios, not risk ratios.

5. Point out the wrong statement:

a) Asymptotics are used for inference usually

b) Adding squared terms makes it continuously differentiable at the knot points

c) Adding squared terms makes it twice continuously differentiable at the knot points

d) None of the Mentioned

View Answer

Explanation: Adding cubic terms makes it twice continuously differentiable at the knot points.

6. Which of the following is example use of Poisson distribution ?

a) Analyzing contigency table data

b) Modeling web traffic hits

c) Incidence rates

d) All of the Mentioned

View Answer

Explanation: The Poisson distribution is a useful model for counts and rates.

7. Principal components or factor analytic models on covariates are often useful for reducing complex covariate spaces.

a) True

b) False

View Answer

Explanation: The space of models explodes quickly as you add interactions and polynomial terms.

8. How many outcomes are possible with bernoulli trial ?

a) 2

b) 3

c) 4

d) None of the Mentioned

View Answer

Explanation: Bernoulli trial is a random experiment with exactly two possible outcomes.

9. Which of the following analysis is a statistical process for estimating the relationships among variables ?

a) Causal

b) Regression

c) Multivariate

d) All of the Mentioned

View Answer

Explanation: Regression models provide the scientist with a powerful tool, allowing predictions about past, present, or future events to be made with information about past or present events.

10. Linear models are the most useful applied statistical technique.

a) True

b) False

View Answer

Explanation: Linear model do have limitations.

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