Top 10 Free Online Courses in Statistics in 2022

This article will discuss the Top 10 Free Online Courses in Statistics and the best free online statistics course with certificates. In previous decades, a career in statistics was almost always associated with a university academic position. On the other hand, data has become a critical component for successful operations due to several multi-disciplinary advances. Furthermore, the emergence of several sub-branches such as data science, big data, and machine learning has become increasingly important in organizations across industries to derive meaningful insights from the massive amounts of data generated every day.

Statistical experts are in high demand across various industries, including universities, sports professionals, finance, healthcare, engineering, technology, marketing and advertising, and e-commerce. The US Bureau of Labor Statistics has identified statisticians as a job trend that will grow faster than most occupations, with an expected growth rate of 33%. As a result of the increased opportunities, now is an excellent time for aspirants to upskill and dive deep into a successful career in some of the most popular industries.

Top 10 Free Online Courses in Statistics

What Is Statistics, and Why Is It Important?

Statistics is a branch of mathematics that deals with the study of data. Population data derived from machine learning, sample distributions, survey results, data analysis, normal distribution, hypothesis testing, research data, and more can all be found in data sets. You may enroll in online statistics courses for a variety of reasons. Aside from being extremely adaptable, there are a number of other benefits that I will outline below.

  • Statistics courses online will give you a solid mathematical understanding of concepts and ideas that aren’t always put into practice.
  • Your computer science skills will benefit from an online statistics course.
  • By allowing you to use computer jargon, these courses will assist you in overcoming application obstacles.
  • They’ll aid in developing your analytical, interpolation, data cleansing, and data-crunching abilities.

Statistics are important because they allow you to understand the characteristics of a small group in comparison to a larger population. You can learn about a large group of people using statistics without having to collect data from everyone.


10 Free Online Courses in Statistics

1. Introduction to Statistics by Stanford University – Coursera

This course is offered through Coursera. This online statistics course focuses on developing solid foundational statistical skills so that learners can effectively work with data and communicate insights. The central limit theorem, descriptive statistics, sampling and randomized controlled experiments, probability, sampling distributions, and the central limit theorem are all topics covered in this course. In addition, key concepts like regression, a common test of significance, and resampling are thoroughly discussed. 

Learners will be able to perform data analysis, distinguish between descriptive and prescriptive statistical concepts, work with data sets, and select appropriate tests for various situations by the end of the course. Learners who want to pursue advanced statistical analysis and machine learning courses will find the concepts covered in this course sufficient. 

2. Advanced Statistics for Data Science Specialization by John Hopkins University – Coursera

On Coursera, you can take a specialization course. The initial modules of the certification program cover fundamental concepts in probability and statistics. A mathematical statistics boot camp is also available, covering the concepts and methods used in biostatistical applications. In addition, the students will learn about advanced linear modeling concepts, data science modeling tools, least-square and linear regression, hypothesis testing, likelihood concepts, and distribution. 

The students will then dive into the practical implementations of the models in order to perform multivariate regression using the R programming language. In addition, the online statistics course provides a solid foundation in linear algebraic requirements for data science and the mathematical perspective of linear statistical models.

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3. Statistics with R Specialization by Duke University – Coursera

This is one of Coursera’s most popular statistics online courses. The course covers key data analysis and visualization concepts in R and how to create repeatable analytical reports. In addition, the students will learn how to make data-driven decisions using statistical inference, Bayesian statistical inference, and modeling. Furthermore, the students will learn how to effectively communicate statistical results and evaluate data-driven decisions and data wrangling with R packages for data analysis.

4. Statistics with Python Specialization by University of Michigan – Coursera

This course is offered through Coursera. The specialization is designed to teach learners how to use Python to learn various statistical concepts. Learners will comprehend data sources, types of data, and the data collection, analysis, and management process. Furthermore, the students will be familiar with data exploration and visualization techniques. Furthermore, the students will delve into data assessment theories, build confidence interval concepts, and interpret inferential results. 

Furthermore, advanced statistical modeling procedures are thoroughly covered, with practical hands-on sessions to help students master the skills. Finally, the students will be able to connect research questions to statistical and data analysis methods in order to solve complex problems in a real-world setting.

5. Data Science: Statistics and Machine Learning Specialization by Johns Hopkins University – Coursera

This online statistics course is available through Coursera. The course is designed for students who have a basic understanding of statistics and machine learning. It covers statistical inference, regression models, and data analysis machine learning algorithms. Learners will also be able to create data products using a variety of tools and techniques, as well as work with real-world data. Furthermore, the students will have a thorough understanding of how to build and apply prediction functions and how to use advanced statistics to draw conclusions about populations and scientific insights from data.

6. Probability and Statistics in Data Science using Python

Probability and Statistics in Data Science with Python is one of the free online statistics courses with credentials. It’s a high-level online statistics course that covers probability and statistics fundamentals. This course will teach you both the mathematical theory and how to use Jupyter notebooks to apply it to real-world data.

7. Learn how to Use Statistics Step-by-step

This course is the foundation of statistics because if you understand it, you will be able to use it throughout the statistical analysis. This free online course on Udemy covers various statistical metrics, including central tendency, deviation measure, variance, standard deviation, moment, skewness, and kurtosis. On the other hand, these factors are used to comprehend a statistical variable fully and grasp various frequency distribution curves, their skewness, and kurtosis using simple explanations and examples. It also teaches students how to use the Lorenz curve and Ginni’s index to visualize and measure distribution inequalities.

8. Intro to Statistics– Udacity

This course for beginners is completely free and covers data visualization, probability, and many basic statistical concepts such as regression, hypothesis testing, etc. This online statistics course will teach you about data visualization and relationships, Bayes Rule and Correlation vs. Causation, Maximum Likelihood estimation, mean, median, and mode, statistical inference, and regression analysis.

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9. Introduction to Statistics– Coursera

Auditing this course is completely free. That means you can get all of the course materials for free. Descriptive Statistics, Sampling and Randomized Controlled Experiments, Probability, Sampling Distributions, and the Central Limit Theorem, Regression, Common Tests of Significance, Resampling, and Multiple Comparisons are all covered in this course. Overall, this course is useful for brushing up on the fundamentals. If you are a complete beginner, you should enroll. It is only necessary to have a basic understanding of computers and productivity software.

10. Intro to Inferential Statistics– Udacity

This is a free statistics course in its entirety. This course will teach you how to use sample statistics, hypothesis testing and confidence intervals, t-tests and ANOVA, correlation and regression, and the chi-squared test to estimate population parameters. Professionals in the industry teach this course, and you will learn through various exercises. If you have a basic understanding of descriptive statistics, you should enroll.

Why Should You Take An Online Statistics Course?

In today’s world of constant innovation, industry competition is at an all-time high. On the other hand, millions of data are generated from various sources every day. Even though new technologies have aided in faster data analysis, statistics experts continue to be a valuable asset to various organizations. Deriving meaningful insights from data to generate business decisions to achieve business goals has become critical in the new era of data-driven decisions in all industries.

Data has become increasingly important in various fields, including weather forecasting, finance, insurance, sports, supply chain, manufacturing, government agencies, life sciences, and healthcare. Appropriate data analysis can provide significant knowledge about evaluating performance and developing future strategies to address challenges or gain a competitive advantage in the market. Furthermore, multidisciplinary fields like data science and big data have created a high demand for statisticians.

Upskilling with the appropriate theoretical and practical skills is required to build a career as a successful statistics professional in multi-disciplinary industries. As a result, it’s critical to choose an online statistics course that exposes students to all of the necessary skills and provides industry-recognized certificates to demonstrate their abilities. As a result, the article highlighted some of the most popular statistics courses available on the internet.

You should be familiar with statistics if you want to work in data science. That’s why I came up with the idea of sharing the 9 Best Free Online Statistics Courses with you. These free statistics courses will assist you in learning statistics. These statistics courses were gathered from a variety of sources. Furthermore, all of the courses are completely free. So, without further ado, let’s begin our search for the Best Free Online Statistics Courses.

Other Free Online Courses for Statistics

1. Introduction to Descriptive Statistics – Udacity Duration

This is Udacity’s third free statistics course. This course will teach you the fundamental terms and concepts of statistics. Also, learn how to calculate and interpret values such as Mean, Median, Mode, Sample, Population, and Standard Deviation. You’ll also learn how to use bar graphs, histograms, box plots, and other common visualizations to explore data. Also how to use distributions to make probabilistic data predictions. If you have a basic understanding of algebra and arithmetic, you should enroll.

2. Bayesian Statistics: From Concept to Data Analysis– Coursera

This is another online statistics course that is available for free to audit. The basics of probability and Bayes’ theorem are covered in this course. The book then goes over statistical inference from both a frequentist and a Bayesian standpoint. After that, you’ll learn how to choose prior distributions and create discrete data models. Finally, this course covers conjugate and objective Bayesian analysis for continuous data. If you have prior knowledge of basic statistics (for example, probability, the Central Limit Theorem, confidence intervals, and linear regression) and calculus, you should enroll.

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3. Introduction to Bayesian Statistics– Udemy

This is a completely free statistics course. You will learn Bayesian statistics from the ground up in this course. You’ll also learn about conditional probability, subjective approaches to probability, and how to model probability problems using Venn and Tree diagrams.

4. Python and Statistics for Financial Analysis– Coursera

Coursera offers a free to audit course. This course combines python programming with statistical concepts. Visualizing and munging stock data, random variables and distribution, sampling and inference, and Linear Regression Models for Financial Analysis are all covered in this online statistics course. You’ll also create a model using multiple global market indices to forecast the price change of an S&P500 ETF. If you have a basic understanding of probability, you should enroll.

5. Statistics literacy for non-statisticians– Udemy

In this online statistics course, you will learn the fundamentals of statistics, such as p-value, ANOVA, variance, and so on. This is not an advanced-level course, and it does not cover the math of the analyses or the software used to conduct them. And you’ll only get a high-level overview of the most important statistical techniques. If you are unfamiliar with statistics but want to learn the basics, you should enroll.

6. Statistics and probability– Khan Academy

This course covers everything from fundamental probability and distributions to more advanced topics like inference and ANOVA models. After reading an Introductory Statistics book like Bayesian Statistics the Fun Way, which is more theoretical and has less code, this course is the best next step. The majority of Khan Academy courses include short, entertaining videos with quizzes. Points are awarded in quizzes. These quizzes will assist you in assessing your statistical knowledge. If you have a basic understanding of math, you should enroll.

List of Free Online Courses on Statistics

Sr. NoCourse NameRatingsPriceCourse Content
$1Math for Middle Schoolers: Statistics4.2/5FreeUnderstand the different statistics topics generally taught in middle school
$2Why Numbers Matter – Online Course4.9/5FreeLearn how to use quantitative research to make difficult decisions and solve real-world problems.
$3Time Series Analysis4.6/5FreeTime series models with real data examples using the R statistical software.
$4Capstone Exam in Statistics and Data Science4.6/5FrThis culminating assessment includes probabilityProbability, data analysis, statistics, and machine learning in this culminating assessment.
$5Data Science: Probability3.9/5FreeGain important foundational knowledge in probability theory essential for a data scientist.
$6Fat Chance: Probability from the Ground Up4.6/5FreeA deeper understanding of probability and statistics.
7I “Heart” Stats: Learning to Love Statistics4.6/5FreeGet to know stats, build a healthy bond, and maybe even fall in love!
8Fundamentals of Statistics4.2/5FreeUnderstanding the principles underpinning statistical inference: estimation, hypothesis testing, and prediction.
9Data Science: Linear Regression4.8/5FreeLearn how to use R to implement linear regression in data science.
10Introduction to Probability – The Science of Uncertainty4.1/5FreeProbabilistic models, including random processes and the basic elements of statistical inference.
11Introduction to Probability: Part 1 – The Fundamentals4/5FreePart 1: Probabilistic models, including random processes and the basic elements of statistical inference.
12Statistics: Unlocking the World of Data4.8/5FreeExplore the ideas and methods behind the statistics you encounter in everyday life.
13Introductory Statistics: Sample Survey and Instruments for Statistical Inference4.9/5FreeThis course aims to introduce basic concepts of sample surveys and to teach the statistical inference process using real-life examples.
14Data Science: Inference and Modeling4.5/5FreeLearn inference and modeling: statistical tools in data analysis.
15Computational Probability and Inference5/5FreeLearn the fundamentals of probabilistic analysis and inference.
16Statistical Modeling and Regression Analysis4.2/5Freelinear regression models along with real data examples using the R.
17Principles, Statistical and Computational Tools for Reproducible Science4.6/5FreeLearn skills and tools that support data science and reproducible research.
18Probability: Distribution Models & Continuous Random Variables4.7/5FreeIncluding normal distribution, and continuous random variables to prepare for a career in information and data science.
19Introduction to Probability4.5/5FreeLearn probability, an essential language and set of tools for understanding data, randomness, and uncertainty.
20Introductory Statistics: Basic Ideas and Instruments for Statistical Inference4.1/5FreeThis course utilizes real-life applications of Statistics in an exploration of the Statistical Inference process.
21Probability – The Science of Uncertainty and Data4.1/5FreeWith this introduction to probabilistic models, data science includes random processes and the basic elements of statistical inference.
22Statistical Inference and Modeling for High-throughput Experiments4.6/5FreeA focus on the techniques commonly used to perform statistical inference on high throughput data.
23Introduction to Probability: Part II? Inference & Processes4.4/5FreeLearn how to use probability theory to develop the basic elements of statistical inference and important random process models
24Introductory Statistics: Analyzing Data Using Graphs and Statistics4.3/5FreeThis course teaches basic statistical concepts and explores many compelling applications of statistical methods using real-life applications of Statistics.
25Statistics for Business – II4.9/5FreeExamine data drawn from allied fields of business such as Finance and HR, and learn how to simulate data to follow a specified distribution.
26Policy Analysis Using Interrupted Time Series4.7/5FreeA comprehensive course on conducting and presenting policy evaluations using interrupted time series analysis.
27Probability: Basic Concepts & Discrete Random Variables4.7/5FreeLearn fundamental concepts of mathematical probability to prepare for a career in the growing field of information and data science.
28Bayesian Statistics3.9/5FreeIn which one’s inferences about parameters or hypotheses are updated as evidence accumulates.
29Statistics for Marketing4.9/5FreeThis course takes a deep dive into the statistical foundation upon which Marketing Analytics is built.
30Introduction to Probability and Data with R4.7/5FreeThis course introduces you to sampling and exploring data and basic probability theory and Bayes’ rule.
31A Crash Course in Causality: Inferring Causal Effects from Observational Data4.8/5FreeWe have all heard the phrase “correlation does not equal causation”.
32An Intuitive Introduction to Probability4.7/5FreeThis course will provide you with an intuitive and practical introduction to Probability Theory.
33Mathematics for Machine Learning: PCA4/5FreeMathematical foundations to derive Principal Component Analysis (PCA), a fundamental dimensionality reduction technique.
34Linear Regression and Modeling4.7/5FreeThis course introduces simple and multiple linear regression models.
35Business Applications of Hypothesis Testing and Confidence Interval Estimation4.8/5FreeConfidence intervals and Hypothesis tests are very important tools in the Business Statistics toolbox.
36Statistics with R Capstone4.7/5FreeThe capstone project will be an analysis using R that answers a specific scientific/business question
37Basic Statistics4.7/5FreeIn this course you will learn the basics of statistics; not just how to calculate them.
38Probability and Statistics: To p or not to p?4.8/5FreeProbability and Statistics: To p or not to p? from the University of London. We live in an uncertain and complex world.
39Methods and Statistics in Social Science – Final Research Project3.9/5FreeThe Final Research Project consists of a research study that you will perform in collaboration with fellow learners.
40Mathematical Biostatistics Boot Camp 14.5/5FreeProbability and statistical concepts are used in elementary data analysis. It will be taught at an introductory level for students with junior.
41Advanced Statistics for Data Science Specialization4.3/5FreeFamiliarize yourself with fundamental concepts in probability and statistics, data analysis, and linear models for Data Science.
42Bayesian Statistics: Techniques and Models4.8/5FreeThis is the second of a two-course sequence introducing the fundamentals of Bayesian statistics.
43Math behind Moneyball4.5/5Freeprobability, math, and statistics can help baseball, football, and basketball teams improve, player and lineup selection, and game strategy.
44Improving your statistical inferences4.9/5FreeDraw better statistical inferences from empirical research. interpret p-values, effect sizes
45Inferential Statistics4.8/5FreeStatistical inference methods for numerical and categorical data.
46Network Dynamics of Social Behavior4.5/5FreeNetwork Dynamics of Social Behavior from the University of Pennsylvania.
47Introduction to Statistics4.5/5FreeThis course is designed to explain the fundamental of statistics. The course contains four weeks or four modules.
48Statistical Learning (Self-Paced)4.5/5FreeThis is an introductory-level course in supervised learning, with a focus on regression and classification methods.
49Introduction to Statistical Inference4.9/5FreeThis course is about, statistical inference is the process of using data analysis to draw conclusions about a population or process beyond the existing data.
50Statistical Reasoning4/5FreeIt is designed for people who want to learn more about Statistics.
51Statistics4.5/5FreeWe live in a time of unprecedented access to information…data.
52Intro to Statistics4.3/5FreeTechniques for visualizing relationships in data and systematic techniques for understanding the relationships using mathematics.
53Intro to Inferential Statistics4.9/5FreeInferential statistics allow us to draw conclusions from data that might not be immediately obvious.
54Intro to Descriptive Statistics3.9/5FreeDescriptive statistics will teach you the basic concepts used to describe data.
55Foundations of Data Science4.5/5Freeearn the fundamental concepts in probability, statistics, optimization, and linear algebra which form the foundations for data science.



I hope that these 10 Best Free Online Statistics Courses will assist you in learning statistics for data science. My goal is to provide you with the best learning resources possible. Please feel free to ask me any questions or concerns in the comments section.

Frequently Asked Questions

What is the definition of statistics?

Statistics is a method for gathering, organizing, analyzing, interpreting, and presenting data to solve a specific problem. It assists you in studying and solving critical problems by employing a variety of methods and data sets.

What are the Best Free Statistics Courses Available on the Internet?

Some of the best free online statistics courses are listed below:
Math for Middle Schoolers: Statistics
Why Numbers Matter – Online Course
Time Series Analysis
Capstone Exam in Statistics and Data Science
Data Science: Probability
Fat Chance: Probability from the Ground Up
Fundamentals of Statistics
Data Science: Linear Regression

What are the Career Options in Statistics? 

In the field of statistics, you can work in the following positions:
Data Analyst
Research Analyst
Data Scientist

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