Data Science

Z-test MCQs with Answers: Interview Questions

In this blog post, you can test your knowledge about Z-test, Z-statistics and related concepts through multiple choice questions (MCQs) and answers. Getting a good understanding of Z-tests, Z-statistics and Z-distribution is of utmost importance for data scientists at large. The following are key concepts around which the MCQs are posted:

  • Z-score or Z-statistics concepts
  • Estimation of population mean and proportion
  • 1-sample Z-test for mean and proportion
  • 2-samples Z-test for mean and proportion

Z-test Interview Questions Samples

The following is a list of interview questions that you would want to learn:

  • What is Z-score? Explain with an example and formula.
  • What are different types of Z-tests? Explain with formula and examples.
  • What is difference between 1-sample and 2-samples Z-test for means? Explain with one example each and formula.
  • What is difference between 1-sample and 2-samples Z-test for proportions? Explain with one example each and formula.
  • How do you estimate population mean at 95% confidence interval as a function of Z-score?
  • How do you estimate population proportion at 95% confidence interval as a function of Z-score?
  • What is standard error? How is it related to margin of error?
  • When to use Z-test and when to use T-test?
  • What is sampling distribution and how is it related to Z-test and Z-statistics?
  • What is Z-distribution? How is this different from T-distribution?
  • What is standard score?
  • How can Z-score be used to compare marks of two students in different classes?

Z-test MCQs Quiz: Questions & Answers

The following is a list of questions and answers aimed to test your knowledge of different types of Z-tests, Z-statistics, hypothesis testing etc.

Ajitesh Kumar

I have been recently working in the area of Data analytics including Data Science and Machine Learning / Deep Learning. I am also passionate about different technologies including programming languages such as Java/JEE, Javascript, Python, R, Julia, etc, and technologies such as Blockchain, mobile computing, cloud-native technologies, application security, cloud computing platforms, big data, etc. For latest updates and blogs, follow us on Twitter. I would love to connect with you on Linkedin. Check out my latest book titled as First Principles Thinking: Building winning products using first principles thinking. Check out my other blog, Revive-n-Thrive.com

Recent Posts

Feature Engineering in Machine Learning: Python Examples

Last updated: 3rd May, 2024 Have you ever wondered why some machine learning models perform…

4 days ago

Feature Selection vs Feature Extraction: Machine Learning

Last updated: 2nd May, 2024 The success of machine learning models often depends on the…

4 days ago

Model Selection by Evaluating Bias & Variance: Example

When working on a machine learning project, one of the key challenges faced by data…

5 days ago

Bias-Variance Trade-off in Machine Learning: Examples

Last updated: 1st May, 2024 The bias-variance trade-off is a fundamental concept in machine learning…

5 days ago

Mean Squared Error vs Cross Entropy Loss Function

Last updated: 1st May, 2024 As a data scientist, understanding the nuances of various cost…

5 days ago

Cross Entropy Loss Explained with Python Examples

Last updated: 1st May, 2024 In this post, you will learn the concepts related to…

5 days ago