HomeRPracticing Statistics Interview Questions in R

# Practicing Statistics Interview Questions in R

In this course, you'll prepare for the most frequently covered statistical topics from distributions to hypothesis testing, regression models, and much more.

4 hours16 videos50 exercises

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## Course Description

Are you job interview ready? You may know everything there is to know about your target company, but have you practiced the classic R statistical interview questions? If not, we have you covered. In this course, you'll prepare for the most frequently covered statistical topics from distributions to hypothesis testing, regression models, and much more. You’ll sharpen your skills using datasets including Parkinson’s disease data and gas prices. This course is purposely more challenging than a typical DataCamp course to make sure that when it comes to interviewing time you’re ready to confidently tackle any statistics interview question in R.

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1. 1

### Probability Distributions

Free

Want to increase your odds of acing your job interview? If so, brush up on your knowledge of probability theory. In this chapter, we'll roll dice and shoot baskets to explain probabilities using real-life examples.

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Discrete distributions
50 xp
Probability functions
100 xp
Bernoulli trials
100 xp
Binomial distribution
100 xp
Continuous distributions
50 xp
Uniform distribution
100 xp
Shape of normal distribution
100 xp
Sample from normal distribution
100 xp
Central limit theorem
50 xp
Law of large numbers
100 xp
Simulating central limit theorem
100 xp
2. 2

### Exploratory Data Analysis

If the job description appeals to you review descriptive statistics before the interview. In this chapter, you will practice exploratory data analysis (EDA) using natural gas prices and data from a survey analysis.

3. 3

### Statistical Tests

March confidently into your job interview after reviewing confidence intervals. We'll review the t-test, ANOVA, and normality tests to prepare you for statistics-based coding questions.

4. 4

### Regression Models

Is your potential employer planning to test your R skills? Make sure you’re prepared and practice model evaluation beforehand. In this chapter, we will fit and evaluate linear and logistic regression models using various biomedical datasets. By the end of this chapter, you’ll be fully prepared to answer any question the interviewer throws your way!

### GroupTraining 2 or more people?

datasets

Natural GasGold monthlyParkinson's DataLetter Recognition

collaborators

Zuzanna Chmielewska

Actuary

Zuzanna is a life insurance actuary and works as an actuarial consultant. In her work, she develops mathematical models for life insurance products in R. Zuzanna obtained her Master's degree in Quantitative Methods in Economics and Information Systems at the Warsaw School of Economics (Poland).
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