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Welcome to the Statistical Inference and Regression Models MCQs Page

Dive deep into the fascinating world of Statistical Inference and Regression Models with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Statistical Inference and Regression Models, a crucial aspect of Data Science. In this section, you will encounter a diverse range of MCQs that cover various aspects of Statistical Inference and Regression Models, from the basic principles to advanced topics. Each question is thoughtfully crafted to challenge your knowledge and deepen your understanding of this critical subcategory within Data Science.

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Check out the MCQs below to embark on an enriching journey through Statistical Inference and Regression Models. Test your knowledge, expand your horizons, and solidify your grasp on this vital area of Data Science.

Note: Each MCQ comes with multiple answer choices. Select the most appropriate option and test your understanding of Statistical Inference and Regression Models. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Statistical Inference and Regression Models MCQs | Page 4 of 8

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Q31.
Which of the following theorem states that the distribution of averages of iid variables, properly normalized, becomes that of a standard normal as the sample size increases?
Discuss
Answer: (a).Central Limit Theorem
Q32.
The binomial random variables are obtained as the sum of iid Gaussian trials.
Discuss
Answer: (a).True
Q33.
The _________ of the Chi-squared distribution is twice the degrees of freedom.
Discuss
Answer: (a).variance
Discuss
Answer: (d).All of the mentioned
Q35.
Gossetโ€™s distribution is invented by which of the following scientist?
Discuss
Answer: (a).William Gosset
Q36.
The _________ of a collection of data is the joint density evaluated as a function of the parameters with the data fixed.
Discuss
Answer: (b).likelihood
Discuss
Answer: (a).Asymptotics generally give assurances about finite sample performance
Discuss
Answer: (d).All of the mentioned
Q39.
CLT is mostly useful as an approximation.
Discuss
Answer: (a).True
Q40.
The beta distribution is the default prior for parameters between ____________
Discuss
Answer: (c).0 and 1
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