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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

Courses

Introduction to Statistics in R

中间的技能水平
4 hours
4.9K
Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data.

Tracks

Statistician in R

52 hours
956
A statistician collects and analyzes data and helps companies make sense of quantitative data, including spotting trends and making predictions.

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Courses

Introduction to Statistics

基本的技能水平
4 hours
9.1K
Learn the fundamentals of statistics, including measures of center and spread, probability distributions, and hypothesis testing with no coding involved!

Courses

Introduction to Statistics in Python

中间的技能水平
4 hours
9.1K
Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data using Python.

Courses

Introduction to Statistics in R

中间的技能水平
4 hours
4.9K
Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data.

Courses

Introduction to Regression in R

中间的技能水平
4 hours
2.8K
Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis in R.

Courses

Hypothesis Testing in Python

中间的技能水平
4 hours
2.4K
Learn how and when to use common hypothesis tests like t-tests, proportion tests, and chi-square tests in Python.

Courses

Sampling in Python

中间的技能水平
4 hours
2.2K
Learn to draw conclusions from limited data using Python and statistics. This course covers everything from random sampling to stratified and cluster sampling.

Courses

Experimental Design in Python

中间的技能水平
4 hours
1.2K
Implement experimental design setups and perform robust statistical analyses to make precise and valid conclusions!

Courses

Time Series Analysis in Python

中间的技能水平
4 hours
1.2K
In this four-hour course, you’ll learn the basics of analyzing time series data in Python.

Courses

Hypothesis Testing in R

中间的技能水平
4 hours
1.2K
Learn how and when to use hypothesis testing in R, including t-tests, proportion tests, and chi-square tests.

Courses

A/B Testing in Python

中间的技能水平
4 hours
1.1K
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.

Courses

Intermediate Regression in R

中间的技能水平
4 hours
966
Learn to perform linear and logistic regression with multiple explanatory variables.

Courses

Sampling in R

中间的技能水平
4 hours
884
Master sampling to get more accurate statistics with less data.

Courses

Linear Algebra for Data Science in R

中间的技能水平
4 hours
824
This course is an introduction to linear algebra, one of the most important mathematical topics underpinning data science.

Courses

Time Series Analysis in R

中间的技能水平
4 hours
791
Learn the core techniques necessary to extract meaningful insights from time series data.

Courses

Foundations of Probability in R

基本的技能水平
4 hours
717
In this course, youll learn about the concepts of random variables, distributions, and conditioning.

Courses

Introduction to Bioconductor in R

中间的技能水平
4 hours
634
Learn to use essential Bioconductor packages for bioinformatics using datasets from viruses, fungi, humans, and plants!

Courses

Introduction to Linear Modeling in Python

中间的技能水平
4 hours
581
Explore the concepts and applications of linear models with python and build models to describe, predict, and extract insight from data patterns.

Courses

Forecasting in R

基本的技能水平
5 hours
575
Learn how to make predictions about the future using time series forecasting in R including ARIMA models and exponential smoothing methods.

Courses

Bayesian Data Analysis in Python

中间的技能水平
4 hours
542
Learn all about the advantages of Bayesian data analysis, and apply it to a variety of real-world use cases!

Courses

Modeling with Data in the Tidyverse

中间的技能水平
4 hours
539
Discover different types in data modeling, including for prediction, and learn how to conduct linear regression and model assessment measures in the Tidyverse.

Courses

Anomaly Detection in Python

中间的技能水平
4 hours
478
Detect anomalies in your data analysis and expand your Python statistical toolkit in this four-hour course.

Courses

RNA-Seq with Bioconductor in R

中间的技能水平
4 hours
472
Use RNA-Seq differential expression analysis to identify genes likely to be important for different diseases or conditions.

Courses

Generalized Linear Models in Python

先进的技能水平
5 hours
426
Extend your regression toolbox with the logistic and Poisson models and learn to train, understand, and validate them, as well as to make predictions.

关于Probability & Statistics相关资源

blogs

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

Tutorials

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

Tutorials

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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