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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

ARIMA Models in R

基本的技能水平
4 hours
337
Become an expert in fitting ARIMA (autoregressive integrated moving average) models to time series data using R.

Courses

Foundations of Inference in R

中间的技能水平
4 hours
329
Learn how to draw conclusions about a population from a sample of data via a process known as statistical inference.

Courses

Statistical Simulation in Python

中间的技能水平
4 hours
311
Learn to solve increasingly complex problems using simulations to generate and analyze data.

Courses

Experimental Design in R

中间的技能水平
4 hours
301
In this course youll learn about basic experimental design, a crucial part of any data analysis.

Courses

Generalized Linear Models in R

中间的技能水平
4 hours
291
The Generalized Linear Model course expands your regression toolbox to include logistic and Poisson regression.

Courses

Analyzing Survey Data in R

中间的技能水平
4 hours
264
Learn survey design using common design structures followed by visualizing and analyzing survey results.

Courses

Foundations of Probability in Python

中间的技能水平
5 hours
260
Learn fundamental probability concepts like random variables, mean and variance, probability distributions, and conditional probabilities.

Courses

Foundations of Inference in Python

先进的技能水平
4 hours
256
Get hands-on experience making sound conclusions based on data in this four-hour course on statistical inference in Python.

Courses

Error and Uncertainty in Google Sheets

中间的技能水平
4 hours
256
Learn to distinguish real differences from random noise, and explore psychological crutches we use that interfere with our rational decision making.

Courses

Survival Analysis in R

中间的技能水平
4 hours
235
Learn to work with time-to-event data. The event may be death or finding a job after unemployment. Learn to estimate, visualize, and interpret survival models!

Courses

Advanced Probability: Uncertainty in Data

先进的技能水平
2 hours
232
Develop a better intuition for advanced probability, risk assessment, and simulation techniques to make data-driven business decisions with confidence.

Courses

A/B Testing in R

中间的技能水平
4 hours
213
Learn the basics of A/B testing in R, including how to design experiments, analyze data, predict outcomes, and present results through visualizations.

Courses

Survival Analysis in Python

先进的技能水平
4 hours
208
Use survival analysis to work with time-to-event data and predict survival time.

Courses

Factor Analysis in R

先进的技能水平
4 hours
201
Explore latent variables, such as personality, using exploratory and confirmatory factor analyses.

Courses

Network Analysis in R

中间的技能水平
4 hours
172
Learn to analyze and visualize network data with the igraph package and create interactive network plots with threejs.

Courses

Case Studies in Statistical Thinking

中间的技能水平
4 hours
141
Take vital steps towards mastery as you apply your statistical thinking skills to real-world data sets and extract actionable insights from them.

Courses

Discrete Event Simulation in Python

先进的技能水平
4 hours
135
Discover the power of discrete-event simulation in optimizing your business processes. Learn to develop digital twins using Pythons SimPy package.

Courses

Practicing Statistics Interview Questions in R

先进的技能水平
4 hours
126
In this course, youll prepare for the most frequently covered statistical topics from distributions to hypothesis testing, regression models, and much more.

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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