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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.

Recommended for Probability & Statistics beginners

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

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Introduction to Statistics in R

IntermediateSkill Level

4 hours

2.6K

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

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Statistician with R

52 hours

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

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74 results

course

Introduction to Statistics in Python

IntermediateSkill Level

4 hours

5.9K

Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data using Python.

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Introduction to Statistics

BeginnerSkill Level

4 hours

4.4K

Learn the fundamentals of statistics, including measures of center and spread, probability distributions, and hypothesis testing with no coding involved!

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Introduction to Statistics in R

IntermediateSkill Level

4 hours

2.6K

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

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Hypothesis Testing in Python

IntermediateSkill Level

4 hours

2.9K

Learn how and when to use common hypothesis tests like t-tests, proportion tests, and chi-square tests in Python.

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Introduction to Regression with statsmodels in Python

IntermediateSkill Level

4 hours

2.4K

Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis with statsmodels in Python.

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Sampling in Python

IntermediateSkill Level

4 hours

2.8K

Learn to draw conclusions from limited data using Python and statistics. This course covers everything from random sampling to stratified and cluster sampling.

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Experimental Design in Python

IntermediateSkill Level

4 hours

1.5K

Implement experimental design setups and perform robust statistical analyses to make precise and valid conclusions!

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Introduction to Regression in R

IntermediateSkill Level

4 hours

1.3K

Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis in R.

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Time Series Analysis in Python

IntermediateSkill Level

4 hours

498

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

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Hypothesis Testing in R

IntermediateSkill Level

4 hours

793

Learn how and when to use hypothesis testing in R, including t-tests, proportion tests, and chi-square tests.

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Statistical Thinking in Python (Part 1)

IntermediateSkill Level

3 hours

588

Build the foundation you need to think statistically and to speak the language of your data.

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Intermediate Regression in R

IntermediateSkill Level

4 hours

729

Learn to perform linear and logistic regression with multiple explanatory variables.

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A/B Testing in Python

IntermediateSkill Level

4 hours

237

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.

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Sampling in R

IntermediateSkill Level

4 hours

759

Master sampling to get more accurate statistics with less data.

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Introduction to Statistics in Google Sheets

BeginnerSkill Level

4 hours

478

Learn how to leverage statistical techniques using spreadsheets to more effectively work with and extract insights from your data.

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RNA-Seq with Bioconductor in R

IntermediateSkill Level

4 hours

142

Use RNA-Seq differential expression analysis to identify genes likely to be important for different diseases or conditions.

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Statistical Techniques in Tableau

IntermediateSkill Level

4 hours

405

Take your reporting skills to the next level with Tableau’s built-in statistical functions.

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Statistical Thinking in Python (Part 2)

IntermediateSkill Level

4 hours

483

Learn to perform the two key tasks in statistical inference: parameter estimation and hypothesis testing.

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Linear Algebra for Data Science in R

IntermediateSkill Level

4 hours

122

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

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Intermediate Regression with statsmodels in Python

IntermediateSkill Level

4 hours

460

Learn to perform linear and logistic regression with multiple explanatory variables.

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Bayesian Data Analysis in Python

IntermediateSkill Level

4 hours

191

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

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Introduction to Bioconductor in R

IntermediateSkill Level

4 hours

173

Learn to use essential Bioconductor packages for bioinformatics using datasets from viruses, fungi, humans, and plants!

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Foundations of Probability in R

BeginnerSkill Level

4 hours

400

In this course, youll learn about the concepts of random variables, distributions, and conditioning.

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Anomaly Detection in Python

IntermediateSkill Level

4 hours

138

Detect anomalies in your data analysis and expand your Python statistical toolkit in this four-hour course.

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Time Series Analysis in R

IntermediateSkill Level

4 hours

189

Learn the core techniques necessary to extract meaningful insights from time series data.

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Foundations of Probability in Python

IntermediateSkill Level

5 hours

320

Learn fundamental probability concepts like random variables, mean and variance, probability distributions, and conditional probabilities.

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Modeling with Data in the Tidyverse

IntermediateSkill Level

4 hours

324

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

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Forecasting in R

IntermediateSkill Level

5 hours

146

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

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Monte Carlo Simulations in Python

IntermediateSkill Level

4 hours

Learn to design and run your own Monte Carlo simulations using Python!

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Customer Analytics and A/B Testing in Python

IntermediateSkill Level

4 hours

112

Learn how to use Python to create, run, and analyze A/B tests to make proactive business decisions.

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Practicing Statistics Interview Questions in Python

AdvancedSkill Level

4 hours

Prepare for your next statistics interview by reviewing concepts like conditional probabilities, A/B testing, the bias-variance tradeoff, and more.

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Fundamentals of Bayesian Data Analysis in R

IntermediateSkill Level

4 hours

132

Learn what Bayesian data analysis is, how it works, and why it is a useful tool to have in your data science toolbox.

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Analyzing Survey Data in R

IntermediateSkill Level

4 hours

172

Learn survey design using common design structures followed by visualizing and analyzing survey results.

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Experimental Design in R

IntermediateSkill Level

4 hours

218

In this course youll learn about basic experimental design, a crucial part of any data analysis.

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Introduction to Linear Modeling in Python

IntermediateSkill Level

4 hours

170

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

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Generalized Linear Models in R

IntermediateSkill Level

4 hours

179

The Generalized Linear Model course expands your regression toolbox to include logistic and Poisson regression.

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Hierarchical and Mixed Effects Models in R

AdvancedSkill Level

4 hours

104

In this course you will learn to fit hierarchical models with random effects.

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Foundations of Inference in R

IntermediateSkill Level

4 hours

161

Learn how to draw conclusions about a population from a sample of data via a process known as statistical inference.

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Introduction to Network Analysis in Python

IntermediateSkill Level

4 hours

This course will equip you with the skills to analyze, visualize, and make sense of networks using the NetworkX library.

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Foundations of Inference in Python

AdvancedSkill Level

4 hours

203

Get hands-on experience making sound conclusions based on data in this four-hour course on statistical inference in Python.

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ARIMA Models in R

IntermediateSkill Level

4 hours

151

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

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Practicing Statistics Interview Questions in R

AdvancedSkill Level

4 hours

In this course, youll prepare for the most frequently covered statistical topics from distributions to hypothesis testing, regression models, and much more.

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Statistical Simulation in Python

IntermediateSkill Level

4 hours

171

Learn to solve increasingly complex problems using simulations to generate and analyze data.

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Survival Analysis in R

IntermediateSkill Level

4 hours

113

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!

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Generalized Linear Models in Python

AdvancedSkill Level

5 hours

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

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Factor Analysis in R

AdvancedSkill Level

4 hours

Explore latent variables, such as personality, using exploratory and confirmatory factor analyses.

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Survival Analysis in Python

AdvancedSkill Level

4 hours

Use survival analysis to work with time-to-event data and predict survival time.

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Structural Equation Modeling with lavaan in R

AdvancedSkill Level

4 hours

Learn how to create and assess measurement models used to confirm the structure of a scale or questionnaire.

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Performing Experiments in Python

IntermediateSkill Level

4 hours

Learn about experimental design, and how to explore your data to ask and answer meaningful questions.

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Network Analysis in R

IntermediateSkill Level

4 hours

Learn to analyze and visualize network data with the igraph package and create interactive network plots with threejs.

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Discrete Event Simulation in Python

AdvancedSkill Level

4 hours

Discover the power of discrete-event simulation in optimizing your business processes. Learn to develop digital twins using Pythons SimPy package.

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Analyzing Survey Data in Python

IntermediateSkill Level

4 hours

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.

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Inference for Linear Regression in R

AdvancedSkill Level

4 hours

117

In this course youll learn how to perform inference using linear models.

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Nonlinear Modeling with Generalized Additive Models (GAMs) in R

AdvancedSkill Level

4 hours

GAMs model relationships in data as nonlinear functions that are highly adaptable to different types of data science problems.

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ChIP-seq with Bioconductor in R

IntermediateSkill Level

4 hours

Learn how to analyse and interpret ChIP-seq data with the help of Bioconductor using a human cancer dataset.

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Differential Expression Analysis with limma in R

AdvancedSkill Level

4 hours

Learn to use the Bioconductor package limma for differential gene expression analysis.

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Inference for Categorical Data in R

AdvancedSkill Level

4 hours

In this course youll learn how to leverage statistical techniques for working with categorical data.

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A/B Testing in R

IntermediateSkill Level

4 hours

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

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Case Study: Analyzing City Time Series Data in R

IntermediateSkill Level

4 hours

Strengthen your knowledge of the topics covered in Manipulating Time Series in R using real case study data.

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Inference for Numerical Data in R

AdvancedSkill Level

4 hours

In this course youll learn techniques for performing statistical inference on numerical data.

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Bayesian Regression Modeling with rstanarm

AdvancedSkill Level

4 hours

Learn how to leverage Bayesian estimation methods to make better inferences about linear regression models.

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Error and Uncertainty in Google Sheets

IntermediateSkill Level

4 hours

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

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Case Studies in Statistical Thinking

IntermediateSkill Level

4 hours

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

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Multivariate Probability Distributions in R

IntermediateSkill Level

4 hours

Learn to analyze, plot, and model multivariate data.

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Bayesian Modeling with RJAGS

AdvancedSkill Level

4 hours

In this course, youll learn how to implement more advanced Bayesian models using RJAGS.

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Intermediate Network Analysis in Python

AdvancedSkill Level

4 hours

Analyze time series graphs, use bipartite graphs, and gain the skills to tackle advanced problems in network analytics.

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Forecasting Product Demand in R

IntermediateSkill Level

4 hours

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.

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Probability Puzzles in R

IntermediateSkill Level

4 hours

Learn strategies for answering probability questions in R by solving a variety of probability puzzles.

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Choice Modeling for Marketing in R

AdvancedSkill Level

4 hours

Learn to analyze and model customer choice data in R.

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Introduction to Anomaly Detection in R

IntermediateSkill Level

4 hours

Learn statistical tests for identifying outliers and how to use sophisticated anomaly scoring algorithms.

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Mixture Models in R

IntermediateSkill Level

4 hours

Learn mixture models: a convenient and formal statistical framework for probabilistic clustering and classification.

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Predictive Analytics using Networked Data in R

IntermediateSkill Level

4 hours

Learn to predict labels of nodes in networks using network learning and by extracting descriptive features from the network

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Building Response Models in R

AdvancedSkill Level

4 hours

Learn to build simple models of market response to increase the effectiveness of your marketing plans.

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Case Studies: Network Analysis in R

BeginnerSkill Level

4 hours

Apply fundamental concepts in network analysis to large real-world datasets in 4 different case studies.

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An Introduction to Statistical Machine Learning

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