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Probability & Statistics courses

Probability and statistics courses explore mathematical concepts for analyzing random events and interpreting data through models and inference. Use tools such as Python, R, Excel and Google Sheets to apply your theoretical knowledge in statistics.

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Recommended for Probability & Statistics beginners

Build your Probability & Statistics skills with interactive courses, curated by real-world experts

课程

Introduction to Statistics in R

中级技能水平
4.4+
4.5K
4 小时
Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data.

学习路径

Statistician in R

919
52 小时
A statistician collects and analyzes data and helps companies make sense of quantitative data, including spotting trends and making predictions.

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课程

Introduction to Statistics

基础技能水平
4.5+
9.7K
4 小时
Learn the fundamentals of statistics, including measures of center and spread, probability distributions, and hypothesis testing with no coding involved!

课程

Introduction to Statistics in Python

中级技能水平
4.5+
8.5K
4 小时
Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data using Python.

课程

Introduction to Statistics in R

中级技能水平
4.4+
4.5K
4 小时
Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data.

课程

Introduction to Regression in R

中级技能水平
4.4+
3.8K
4 小时
Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis in R.

课程

Hypothesis Testing in Python

中级技能水平
4.5+
2.4K
4 小时
Learn how and when to use common hypothesis tests like t-tests, proportion tests, and chi-square tests in Python.

课程

Sampling in Python

中级技能水平
4.5+
2.2K
4 小时
Learn to draw conclusions from limited data using Python and statistics. This course covers everything from random sampling to stratified and cluster sampling.

课程

Hypothesis Testing in R

中级技能水平
4.3+
1.8K
4 小时
Learn how and when to use hypothesis testing in R, including t-tests, proportion tests, and chi-square tests.

课程

Intermediate Regression in R

中级技能水平
4.4+
1.5K
4 小时
Learn to perform linear and logistic regression with multiple explanatory variables.

课程

Time Series Analysis in Python

中级技能水平
4.4+
1.2K
4 小时
In this four-hour course, you’ll learn the basics of analyzing time series data in Python.

课程

Experimental Design in Python

中级技能水平
4.5+
1.1K
4 小时
Implement experimental design setups and perform robust statistical analyses to make precise and valid conclusions!

课程

Sampling in R

中级技能水平
4.3+
1K
4 小时
Master sampling to get more accurate statistics with less data.

课程

Time Series Analysis in R

中级技能水平
4.6+
940
4 小时
Learn the core techniques necessary to extract meaningful insights from time series data.

课程

ARIMA Models in R

基础技能水平
4.6+
841
4 小时
Become an expert in fitting ARIMA (autoregressive integrated moving average) models to time series data using R.

课程

Forecasting in R

基础技能水平
4.4+
832
5 小时
Learn how to make predictions about the future using time series forecasting in R including ARIMA models and exponential smoothing methods.

课程

A/B Testing in Python

中级技能水平
4.4+
797
4 小时
Learn the practical uses of A/B testing in Python to run and analyze experiments. Master p-values, sanity checks, and analysis to guide business decisions.

课程

Modeling with Data in the Tidyverse

中级技能水平
4.3+
716
4 小时
Discover different types in data modeling, including for prediction, and learn how to conduct linear regression and model assessment measures in the Tidyverse.

课程

Foundations of Probability in R

基础技能水平
4.5+
661
4 小时
In this course, youll learn about the concepts of random variables, distributions, and conditioning.

课程

Linear Algebra for Data Science in R

中级技能水平
4.4+
652
4 小时
This course is an introduction to linear algebra, one of the most important mathematical topics underpinning data science.

课程

Introduction to Bioconductor in R

中级技能水平
4.4+
548
4 小时
Learn to use essential Bioconductor packages for bioinformatics using datasets from viruses, fungi, humans, and plants!

课程

Generalized Linear Models in R

中级技能水平
4.5+
514
4 小时
The Generalized Linear Model course expands your regression toolbox to include logistic and Poisson regression.

课程

Introduction to Linear Modeling in Python

中级技能水平
4.6+
512
4 小时
Explore the concepts and applications of linear models with python and build models to describe, predict, and extract insight from data patterns.

课程

Statistical Techniques in Tableau

中级技能水平
4.6+
508
4 小时
Take your reporting skills to the next level with Tableau’s built-in statistical functions.

课程

Bayesian Data Analysis in Python

中级技能水平
4.6+
506
4 小时
Learn all about the advantages of Bayesian data analysis, and apply it to a variety of real-world use cases!

课程

Foundations of Inference in R

中级技能水平
4.4+
504
4 小时
Learn how to draw conclusions about a population from a sample of data via a process known as statistical inference.

课程

RNA-Seq with Bioconductor in R

中级技能水平
4.4+
473
4 小时
Use RNA-Seq differential expression analysis to identify genes likely to be important for different diseases or conditions.

课程

Generalized Linear Models in Python

高级技能水平
4.6+
433
5 小时
Extend your regression toolbox with the logistic and Poisson models and learn to train, understand, and validate them, as well as to make predictions.

Probability & Statistics 相关资源

博客

How to Become a Statistician in 2026

Curious about how to become a statistician? Find out what a statistician does, what you need to get started, and what you can expect from this career.
Joleen Bothma's photo

Joleen Bothma

10分钟

教程

An Introduction to Statistical Machine Learning

Discover the powerful fusion of statistics and machine learning. Explore how statistical techniques underpin machine learning models, enabling data-driven decision-making.
Joanne Xiong's photo

Joanne Xiong

11分钟

教程

T-tests in R Tutorial: Learn How to Conduct T-Tests

Determine if there is a significant difference between the means of the two groups using t.test() in R.
Abid Ali Awan's photo

Abid Ali Awan

10分钟

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    Frequently asked questions

    How does probability and statistics related to data science?

    Probability and statistics are foundational to data science, offering the tools and frameworks necessary for analyzing data, making predictions, and deriving meaningful insights. They enable data scientists to understand patterns, assess uncertainties, and make informed decisions based on data analysis.

    Why is it important to develop knowledge in probability and statistics?

    Developing knowledge in probability and statistics is crucial for effectively interpreting data and making reliable predictions. This understanding forms the basis for designing experiments, analyzing results, and validating conclusions in various fields, ensuring decisions are data-driven and evidence-based.

    What careers can I pursue with knowledge in probability and statistics?

    With knowledge in probability and statistics, you can pursue a wide array of careers such as data scientist, market researcher, machine learning engineer, statistical analyst, and risk manager. These roles span various industries including finance, healthcare, technology, and government, where interpreting data and making evidence-based decisions are key.

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