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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

Course

Introduction to Statistics in R

4 hr
2.6K
Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data.

Track

Statistician with R

52 hr
26
A statistician collects and analyzes data and helps companies make sense of quantitative data, including spotting trends and making predictions.

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70 results

Course

Introduction to Statistics in Python

IntermediateSkill Level
4 hr
5.4K
Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data using Python.

Course

Introduction to Statistics

BeginnerSkill Level
4 hr
4.3K
Learn the fundamentals of statistics, including measures of center and spread, probability distributions, and hypothesis testing with no coding involved!

Course

Introduction to Statistics in R

IntermediateSkill Level
4 hr
2.6K
Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data.

Course

Introduction to Regression in R

IntermediateSkill Level
4 hr
2.3K
Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis in R.

Course

Hypothesis Testing in Python

IntermediateSkill Level
4 hr
2.4K
Learn how and when to use common hypothesis tests like t-tests, proportion tests, and chi-square tests in Python.

Course

Sampling in Python

IntermediateSkill Level
4 hr
2.3K
Learn to draw conclusions from limited data using Python and statistics. This course covers everything from random sampling to stratified and cluster sampling.

Course

Intermediate Regression in R

IntermediateSkill Level
4 hr
1.2K
Learn to perform linear and logistic regression with multiple explanatory variables.

Course

Time Series Analysis in Python

IntermediateSkill Level
4 hr
733
In this four-hour course, you’ll learn the basics of analyzing time series data in Python.

Course

Hypothesis Testing in R

IntermediateSkill Level
4 hr
1K
Learn how and when to use hypothesis testing in R, including t-tests, proportion tests, and chi-square tests.

Course

A/B Testing in Python

IntermediateSkill Level
4 hr
318
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.

Course

Sampling in R

IntermediateSkill Level
4 hr
847
Master sampling to get more accurate statistics with less data.

Course

Time Series Analysis in R

IntermediateSkill Level
4 hr
503
Learn the core techniques necessary to extract meaningful insights from time series data.

Course

Bayesian Data Analysis in Python

IntermediateSkill Level
4 hr
211
Learn all about the advantages of Bayesian data analysis, and apply it to a variety of real-world use cases!

Course

Generalized Linear Models in R

IntermediateSkill Level
4 hr
288
The Generalized Linear Model course expands your regression toolbox to include logistic and Poisson regression.

Course

Analyzing Survey Data in R

IntermediateSkill Level
4 hr
194
Learn survey design using common design structures followed by visualizing and analyzing survey results.

Course

Modeling with Data in the Tidyverse

IntermediateSkill Level
4 hr
437
Discover different types in data modeling, including for prediction, and learn how to conduct linear regression and model assessment measures in the Tidyverse.

Course

Introduction to Linear Modeling in Python

IntermediateSkill Level
4 hr
354
Explore the concepts and applications of linear models with python and build models to describe, predict, and extract insight from data patterns.

Course

Anomaly Detection in Python

IntermediateSkill Level
4 hr
192
Detect anomalies in your data analysis and expand your Python statistical toolkit in this four-hour course.

Course

Foundations of Probability in Python

IntermediateSkill Level
5 hr
252
Learn fundamental probability concepts like random variables, mean and variance, probability distributions, and conditional probabilities.

Course

Foundations of Probability in R

BeginnerSkill Level
4 hr
483
In this course, you'll learn about the concepts of random variables, distributions, and conditioning.

Course

Experimental Design in R

IntermediateSkill Level
4 hr
388
In this course you'll learn about basic experimental design, a crucial part of any data analysis.

Course

Forecasting in R

IntermediateSkill Level
5 hr
230
Learn how to make predictions about the future using time series forecasting in R including ARIMA models and exponential smoothing methods.

Course

Foundations of Inference in R

IntermediateSkill Level
4 hr
319
Learn how to draw conclusions about a population from a sample of data via a process known as statistical inference.

Course

ARIMA Models in R

IntermediateSkill Level
4 hr
294
Become an expert in fitting ARIMA (autoregressive integrated moving average) models to time series data using R.

Course

Network Analysis in R

IntermediateSkill Level
4 hr
221
Learn to analyze and visualize network data with the igraph package and create interactive network plots with threejs.

Course

Linear Algebra for Data Science in R

IntermediateSkill Level
4 hr
111
This course is an introduction to linear algebra, one of the most important mathematical topics underpinning data science.

Course

Analyzing Survey Data in Python

IntermediateSkill Level
4 hr
178
Learn how to analyze survey data with Python and discover when it is appropriate to apply statistical tools that are descriptive and inferential in nature.

Course

Factor Analysis in R

AdvancedSkill Level
4 hr
114
Explore latent variables, such as personality, using exploratory and confirmatory factor analyses.

Course

Generalized Linear Models in Python

AdvancedSkill Level
5 hr
154
Extend your regression toolbox with the logistic and Poisson models and learn to train, understand, and validate them, as well as to make predictions.

Course

Performing Experiments in Python

IntermediateSkill Level
4 hr
86
Learn about experimental design, and how to explore your data to ask and answer meaningful questions.

Course

Survival Analysis in R

IntermediateSkill Level
4 hr
117
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!

Course

Foundations of Inference in Python

AdvancedSkill Level
4 hr
165
Get hands-on experience making sound conclusions based on data in this four-hour course on statistical inference in Python.

Course

Survival Analysis in Python

AdvancedSkill Level
4 hr
60
Use survival analysis to work with time-to-event data and predict survival time.

Course

Error and Uncertainty in Google Sheets

IntermediateSkill Level
4 hr
135
Learn to distinguish real differences from random noise, and explore psychological crutches we use that interfere with our rational decision making.

Course

Business Process Analytics in R

IntermediateSkill Level
4 hr
109
Learn how to analyze business processes in R and extract actionable insights from enormous sets of event data.

Course

A/B Testing in R

IntermediateSkill Level
4 hr
35
Learn the basics of A/B testing in R, including how to design experiments, analyze data, predict outcomes, and present results through visualizations.

Course

Case Studies in Statistical Thinking

IntermediateSkill Level
4 hr
50
Take vital steps towards mastery as you apply your statistical thinking skills to real-world data sets and extract actionable insights from them.

Course

Forecasting Product Demand in R

IntermediateSkill Level
4 hr
45
Learn how to identify important drivers of demand, look at seasonal effects, and predict demand for a hierarchy of products from a real world example.

Course

Practicing Statistics Interview Questions in R

AdvancedSkill Level
4 hr
23
In this course, you'll prepare for the most frequently covered statistical topics from distributions to hypothesis testing, regression models, and much more.

Course

Bayesian Modeling with RJAGS

AdvancedSkill Level
4 hr
34
In this course, you'll learn how to implement more advanced Bayesian models using RJAGS.

Course

Building Response Models in R

AdvancedSkill Level
4 hr
58
Learn to build simple models of market response to increase the effectiveness of your marketing plans.

Course

Mixture Models in R

IntermediateSkill Level
4 hr
12
Learn mixture models: a convenient and formal statistical framework for probabilistic clustering and classification.

Course

Experimental Design in Python

IntermediateSkill Level
4 hr
27
Implement experimental design setups and perform robust statistical analyses to make precise and valid conclusions!

Course

Probability Puzzles in R

IntermediateSkill Level
4 hr
9
Learn strategies for answering probability questions in R by solving a variety of probability puzzles.
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Related resources on Probability & Statistics

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How to Become a Statistician in 2023

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An Introduction to Statistical Machine Learning

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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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