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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.

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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.

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  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.

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  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!

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GroupTraining 2 or more people?

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Datasets

Natural GasGold monthlyParkinson's DataLetter Recognition

Collaborators

Collaborator's avatar
Anneleen Beckers
Collaborator's avatar
Maggie Matsui
Zuzanna Chmielewska HeadshotZuzanna 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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