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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

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Introduction to Statistics in R

IntermediateSkill Level
4 hours
2.2K
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
24
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

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Introduction to Statistics in Python

IntermediateSkill Level
4 hours
5.3K
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
3.9K
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
2.2K
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
2.6K
Learn how and when to use common hypothesis tests like t-tests, proportion tests, and chi-square tests in Python.

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Sampling in Python

IntermediateSkill Level
4 hours
2.7K
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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Introduction to Regression in R

IntermediateSkill Level
4 hours
1.5K
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
647
In this four-hour course, you’ll learn the basics of analyzing time series data in Python.

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Experimental Design in Python

IntermediateSkill Level
4 hours
754
Implement experimental design setups and perform robust statistical analyses to make precise and valid conclusions!

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Hypothesis Testing in R

IntermediateSkill Level
4 hours
830
Learn how and when to use hypothesis testing in R, including t-tests, proportion tests, and chi-square tests.

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Intermediate Regression in R

IntermediateSkill Level
4 hours
774
Learn to perform linear and logistic regression with multiple explanatory variables.

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Sampling in R

IntermediateSkill Level
4 hours
773
Master sampling to get more accurate statistics with less data.

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A/B Testing in Python

IntermediateSkill Level
4 hours
221
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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Statistical Techniques in Tableau

IntermediateSkill Level
4 hours
460
Take your reporting skills to the next level with Tableau’s built-in statistical functions.

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RNA-Seq with Bioconductor in R

IntermediateSkill Level
4 hours
158
Use RNA-Seq differential expression analysis to identify genes likely to be important for different diseases or conditions.

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Bayesian Data Analysis in Python

IntermediateSkill Level
4 hours
243
Learn all about the advantages of Bayesian data analysis, and apply it to a variety of real-world use cases!

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Foundations of Probability in Python

IntermediateSkill Level
5 hours
353
Learn fundamental probability concepts like random variables, mean and variance, probability distributions, and conditional probabilities.

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Analyzing Survey Data in R

IntermediateSkill Level
4 hours
188
Learn survey design using common design structures followed by visualizing and analyzing survey results.

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Time Series Analysis in R

IntermediateSkill Level
4 hours
261
Learn the core techniques necessary to extract meaningful insights from time series data.

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Introduction to Bioconductor in R

IntermediateSkill Level
4 hours
163
Learn to use essential Bioconductor packages for bioinformatics using datasets from viruses, fungi, humans, and plants!

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Generalized Linear Models in R

IntermediateSkill Level
4 hours
245
The Generalized Linear Model course expands your regression toolbox to include logistic and Poisson regression.

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Anomaly Detection in Python

IntermediateSkill Level
4 hours
142
Detect anomalies in your data analysis and expand your Python statistical toolkit in this four-hour course.

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Foundations of Probability in R

BeginnerSkill Level
4 hours
391
In this course, youll learn about the concepts of random variables, distributions, and conditioning.

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Forecasting in R

IntermediateSkill Level
5 hours
202
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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Introduction to Linear Modeling in Python

IntermediateSkill Level
4 hours
172
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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Experimental Design in R

IntermediateSkill Level
4 hours
285
In this course youll learn about basic experimental design, a crucial part of any data analysis.

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Foundations of Inference in R

IntermediateSkill Level
4 hours
198
Learn how to draw conclusions about a population from a sample of data via a process known as statistical inference.

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Modeling with Data in the Tidyverse

IntermediateSkill Level
4 hours
301
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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ARIMA Models in R

IntermediateSkill Level
4 hours
220
Become an expert in fitting ARIMA (autoregressive integrated moving average) models to time series data using R.

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Linear Algebra for Data Science in R

IntermediateSkill Level
4 hours
67
This course is an introduction to linear algebra, one of the most important mathematical topics underpinning data science.

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Survival Analysis in R

IntermediateSkill Level
4 hours
124
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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Statistical Simulation in Python

IntermediateSkill Level
4 hours
113
Learn to solve increasingly complex problems using simulations to generate and analyze data.

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Foundations of Inference in Python

AdvancedSkill Level
4 hours
175
Get hands-on experience making sound conclusions based on data in this four-hour course on statistical inference in Python.

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Network Analysis in R

IntermediateSkill Level
4 hours
113
Learn to analyze and visualize network data with the igraph package and create interactive network plots with threejs.

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Survival Analysis in Python

AdvancedSkill Level
4 hours
45
Use survival analysis to work with time-to-event data and predict survival time.

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Performing Experiments in Python

IntermediateSkill Level
4 hours
68
Learn about experimental design, and how to explore your data to ask and answer meaningful questions.

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Factor Analysis in R

AdvancedSkill Level
4 hours
80
Explore latent variables, such as personality, using exploratory and confirmatory factor analyses.

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Generalized Linear Models in Python

AdvancedSkill Level
5 hours
57
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

Error and Uncertainty in Google Sheets

IntermediateSkill Level
4 hours
143
Learn to distinguish real differences from random noise, and explore psychological crutches we use that interfere with our rational decision making.

course

Analyzing Survey Data in Python

IntermediateSkill Level
4 hours
68
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

A/B Testing in R

IntermediateSkill Level
4 hours
54
Learn the basics of A/B testing in R, including how to design experiments, analyze data, predict outcomes, and present results through visualizations.

course

Discrete Event Simulation in Python

AdvancedSkill Level
4 hours
39
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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Forecasting Product Demand in R

IntermediateSkill Level
4 hours
72
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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Case Studies in Statistical Thinking

IntermediateSkill Level
4 hours
47
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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ChIP-seq with Bioconductor in R

IntermediateSkill Level
4 hours
23
Learn how to analyse and interpret ChIP-seq data with the help of Bioconductor using a human cancer dataset.

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Bayesian Modeling with RJAGS

AdvancedSkill Level
4 hours
36
In this course, youll learn how to implement more advanced Bayesian models using RJAGS.

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Practicing Statistics Interview Questions in R

AdvancedSkill Level
4 hours
18
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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Mixture Models in R

IntermediateSkill Level
4 hours
10
Learn mixture models: a convenient and formal statistical framework for probabilistic clustering and classification.

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Building Response Models in R

AdvancedSkill Level
4 hours
26
Learn to build simple models of market response to increase the effectiveness of your marketing plans.

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Probability Puzzles in R

IntermediateSkill Level
4 hours
12
Learn strategies for answering probability questions in R by solving a variety of probability puzzles.
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Related resources on Probability & Statistics

blog

How to Become a Statistician in 2023

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.
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Joleen Bothma

10 min

tutorial

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.
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Joanne Xiong

11 min

tutorial

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.
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Abid Ali Awan

10 min

Ready to apply your skills?

Projects allow you to apply your knowledge to a wide range of datasets to solve real-world problems in your browser

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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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