#### Questions on Basic Terminology

- Why study Statistics?
- What is the difference between Population and Sample?
- What do you understand by census and Survey?
- How to describe Parameter and Statistics?
- How to define Descriptive vs Inferential Statistics? Explain with an example.
- Types of variables in Statistics?
- Difference between Nominal vs Ordinal variables and discrete vs Continuous variables.
- What are the measures of Central Tendencies? Explain with suitable examples.
- Describe with specific examples on when to use mean, when to use median and when to use mode?
- Explain the measures of variability and spread with example?
- What is the mathematical significance variance and Standard Deviation and how to calculate them?
- How to define Outliers in your data set and what are the techniques to deal with outliers?
- Explain the Box Plot.
- Describe z-score also known as a standard score.

#### Questions on Probability Basics

- Probability vs Statistics
- Explain about Joint Probability, Union Probability and Marginal Probability.
- Explain about Mutually exclusive vs Independent Events.
- Conditional Probability use cases in Data Science.
- What is the Monty Hall Problem?
- Explain the use and importance of Bayes’ Theorem in Data Science study.

#### Performance Metrics

- Explain what is confusion matrix and various terms associated with it.
- What is Recall and how it is different from Precision? Give examples of each.
- What is the True Positive Rate?
- How to differentiate between F1 Score and Accuracy?

#### Probability Distributions

- Describe Probability Distribution Function (PDF) and Probability Mass Function (PMF).
- Describe skewed vs normally distributed Data.
- What is Kurtosis?
- What is Bernoulli distribution and How is different from Geometric Distribution?
- What is Binomial Distribution?
- What is Exponential Distribution and how it is different from Poisson distribution?
- What are the properties of Normal or Gaussian distribution?

#### Advanced Statistics Questions

- Explain the usage of Central Limit Theorem in Data Science.
- What are the three important properties of Central Limit Theorem?
- What do you mean by Sampling Distribution?
- What is the Standard error of the Mean?
- Explain Confidence Level and Confidence Interval.
- What is the difference between Standard Error and Margin of error? Are the Same?
- Explain Hypothesis Testing.
- What is significance Level in Hypothesis Testing?
- How to determine the Critical Region?
- What are p-value and q-value?
- How to validate the Null Hypothesis?
- What do you understand by one-tailed and two-tailed test in hypothesis testing?
- Explain about Type I and Type II errors.
- What are the tests done to check the sampling distribution of means?
- Explain the z test and t-test and their properties.
- What are the tests done to check the Sampling Distribution of Variance?
- Explain X-Square (Chi-Squared) and F test and their properties.
- What do you understand by “Goodness of Fit”?
- Explain the use case of ANOVA.