课程

Practicing Statistics Interview Questions in R

高级技能水平

更新时间 2022年10月

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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RProbability & Statistics4 小时16 视频50 练习4,200 经验值4,613成就声明

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课程描述

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.

先决条件

Intermediate R Foundations of Inference in R Foundations of Probability in R

1

Probability Distributions

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.

Discrete distributions

50 经验值

Probability functions

100 经验值

Bernoulli trials

100 经验值

Binomial distribution

100 经验值

Continuous distributions

50 经验值

Uniform distribution

100 经验值

Shape of normal distribution

100 经验值

Sample from normal distribution

100 经验值

Central limit theorem

50 经验值

Law of large numbers

100 经验值

Simulating central limit theorem

100 经验值

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.

Descriptive statistics

50 经验值

Centrality measures

100 经验值

Variability measures

100 经验值

Categorical data

50 经验值

Survey analysis

100 经验值

Data encoding

100 经验值

Time series

50 经验值

Time series object

100 经验值

Wrangling time series

100 经验值

Principal Component Analysis

50 经验值

PCA - rotation

100 经验值

PCA - dimension reduction

100 经验值

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.

Normality tests

50 经验值

Shapiro-Wilk test

100 经验值

100 经验值

Inference for a mean

50 经验值

Confidence interval

100 经验值

One-sample t-test

100 经验值

Comparing two means

50 经验值

Two-sample t-test

100 经验值

Paired test

100 经验值

50 经验值

Comparing groups

100 经验值

ANOVA for plant growth

100 经验值

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!

Covariance and correlation

50 经验值

Covariance by hand

100 经验值

Linear relationship

100 经验值

Nonlinear relationship

100 经验值

Linear regression model

50 经验值

Fitting linear models

100 经验值

Predicting with linear models

100 经验值

Logistic regression model

50 经验值

Fitting logistic models

100 经验值

Predicting with logistic models

100 经验值

Model evaluation

50 经验值

Validation set approach

100 经验值

Regression evaluation

100 经验值

Classification evaluation

100 经验值

Wrapping up

50 经验值

Practicing Statistics Interview Questions in R

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