9 Best Free Online Courses for Statistics for Data Science in 2024

For data science, you should have a good understanding of Statistics. That’s why I thought to share the 9 Best Free Online Courses for Statistics with you. These statistics courses will help you to learn statistics free of cost. I have collected these statistics courses from various platforms. And all courses are completely free.

So without any further ado, let’s start finding the Best Free Online Courses for Statistics.

Best Free Online Courses for Statistics

1. Intro to Statistics– Udacity

Rating	NA
Time to Complete-	2 Months
Best For-	Beginners

This Intro to Statistics is a completely FREE course for beginners. This course is taught by Udacity Co-Founder, Sebastian Thrun. The course structure is interesting and fun for beginners. The course begins with a teaser where Sebastian Thrun gives a challenging teaser.

Throughout the course, you will learn the statistics basics and understand charts, plots, and probability basics.

Along with that, you will also learn Central Limit Theorem, Normal Distribution, Confidence Interval, Hypothesis Test, Regression, etc. This course has 6 problem sets and various quizzes related to statistics.

At the end of this course, there is one final exam, where there are 16 questions. And you have to answer these questions by yourself.

Pros-

• You don’t need to pay for this course.
• The course covers theory as well as practical exercises.

Cons-

• You will not receive a Certificate after completing the course.

You Should Enroll if-

• You are a beginner, but it’s good if you have already heard of some easy statistical concepts.

Interested to Enroll?

If yes, then start learning- Intro to Statistics

2. Introduction to Statistics- Coursera

Rating	4.5/5
Time to Complete-	15 hours
Best For-	Beginners
Provider-	Standford University

This Introduction to Statistics course is Free to Audit. That means you can access the full course material free of cost. To Audit the course for free, click on the “Enroll for Free” button. You will see the two options- “Purchase Course” and “Full Course, No Certificate”. Choose the second option and you will be redirected to the course material.

This course is divided into an 8-week study plan. The course begins with a basic introduction to the course material and statistics. Next, you will learn Sampling and Probability basics such as Bayes’ Rule.

In this course, you will also learn Regression, Correlation, Residuals, Confidence Interval, Tests of Significance, etc. The Monte Carlo method is also explained in this course.

Pros-

• There are 12 quizzes in this course, which are unlocked. Usually, Coursera doesn’t unlock quizzes for Free courses, but in this course, you can access the quizzes too.

Cons-

• This course will not provide a certificate after completing the course.

You Should Enroll if-

• You are a complete beginner. Only basic familiarity with computers and productivity software is required.

Interested to Enroll?

If yes, then start learning- Introduction to Statistics

3. Intro to Descriptive Statistics- Udacity

Rating	NA
Time to Complete-	2 Months
Best For-	Beginners

This Intro to Descriptive Statistics is a complete Free course for statistics. The course begins with an intro to Research Methods, where you will understand how to Measure Memory and Define Constructs. The first lesson is very insightful where you will get to know about the Golden Arches Theory of Conflict Prevention.

Throughout the course, there are various MCQ questions, which you have to answer.

After that, you will learn how to visualize the data and work on a problem set. This course also covers Skewed Distribution.

The last part of this course covers Variability, Standardizing, and Distributions. Along with these courses, there are problem sets associated. There is a separate lesson on Google Spreadsheet Tutorial.

Overall, this is a good course to learn and practice Descriptive Statistics.

Pros-

• The course uses real-world examples to clear the concepts.
• Various exercises and quizzes are in this course.

Cons-

• Doesn’t provide a certificate.

You Should Enroll if-

• You have a basic understanding of basic algebra and arithmetic.

Interested to Enroll?

If yes, then start learning- Intro to Descriptive Statistics

4. Intro to Inferential Statistics– Udacity

Rating	NA
Time to Complete-	2 Months
Best For-	Intermediate

Time to Complete- 2 Months

This Intro to Inferential Statistics is the third Free statistics course at Udacity. This course is the next follow-up course of the “Intro to Descriptive Statistics“. If you have not previously watched the descriptive statistics course, first watch the Intro to Descriptive Statistics course.

The course begins with the explanation of Klout Sampling Distribution (Mean), Klout Sampling Distribution (SD), Sampling Distribution Shape, Probability of Obtaining Mean, etc.

Along with that, you will learn Hypothesis Testing, t-Tests, ANOVA, Correlation, and Regression. There are also quizzes and exercises throughout the course to test your understanding.

Pros-

• The course is in-depth and the instructor uses a visual representation to teach the concepts of statistics.

Cons-

• Only the course content is free. You will not receive a certificate after completing the course.

You Should Enroll if-

• You have an understanding of Descriptive Statistics.

Interested to Enroll?

If yes, then start learning- Intro to Inferential Statistics

5. Bayesian Statistics: From Concept to Data Analysis- Coursera

Rating	4.6/5
Time to Complete-	12 hours
Best For-	Intermediate
Provider-	University of California, Santa Cruz

This Bayesian Statistics: From Concept to Data Analysis is another Free to Audit course for statistics. The course is divided into a 4-week study plan.

This course begins with the basics of probability and Bayes’ theorem. Next, the instructor explains Statistical Inference and R Programming basics. You will learn how to plot a likelihood in R and Excel.

You will also learn Priors, Poisson Data, and Linear Regression. This is a short course, not too lengthy course.

Pros-

• This course provides supplementary materials for reading.

Cons-

• The quizzes and exercises are locked in the free course. To get access to the quizzes, you need to purchase a Coursera subscription.

You Should Enroll if-

• You should have prior knowledge of basic statistics class (for example, probability, the Central Limit Theorem, confidence intervals, linear regression) and calculus (integration and differentiation).

Interested to Enroll?

If yes, then start learning- Bayesian Statistics: From Concept to Data Analysis

6. Introduction to Bayesian Statistics- Udemy

Rating	4.8/5
Time to Complete-	1hr 19min
Best For-	Beginner

This Introduction to Bayesian Statistics is a completely Free course for statistics. There are 4 sections in this course. The first section is a short introduction to Bayesian Statistics. The next section covers probability basics and there is one quiz associated with this section. In this quiz, there are two MCQ questions.

After that, you will learn Conditional Probability and Normal Distribution. There are 3 quizzes on Conditional probability and Tree diagrams.

At the end of this course, you will understand Bayes’ Theorem.

Pros-

• The explanation of this course is easier to understand.

Cons-

• Some of the concepts are hard to understand for beginners.

You Should Enroll if-

• You are a beginner and want to understand Bayesian statistics more deeply.

Interested to Enroll?

If yes, then start learning- Introduction to Bayesian Statistics

7. Python and Statistics for Financial Analysis- Coursera

Rating	4.4/5
Time to Complete-	13 hours
Best For-	Intermediate
provider–	The Hong Kong University of Science and Technology

This “Python and Statistics for Financial Analysis” is a Free to Audit course by Coursera. This course has a 4-week study plan. In week 1, you will learn different packages for data analysis, how to import data from CSV files to Jupyter Notebook, and Dataframes.

Week 2 is not very time-consuming and has only 19 minutes of lectures, where you will learn Random Variables, Frequency, and Distributions.

After that, you will understand Confidence Interval, Hypothesis testing, and P-value. Throughout the course, there are quizzes that you can complete to test your understanding.

At the end of this course, you will learn Simple Linear Regression and Multiple Linear Regression. In quizzes, all questions are in MCQ form.

Pros-

• The quizzes and assignments are unlocked for the free course.

Cons-

• You will not receive a course certificate.

You Should Enroll if-

• You have basic knowledge of probability.

Interested to Enroll?

If yes, then start learning- Python and Statistics for Financial Analysis

8. Statistics literacy for non-statisticians- Udemy

Rating	4.7/5
Time to Complete-	1hr 36min
Best For-	Beginner

In this “Statistics literacy for non-statisticians“ Free course, there are 5 sections. In the first section, you will learn about Data Visualization and measures of central tendency (mean, median, mode). After that, you will learn the probability basics and hypothesis testing.

At the end of this course, you will understand statistical tests such as t-test, correlation, ANOVA, and Regression. This is not a very detailed course on statistics but good for understanding the basics.

Pros-

• Good course to revise your statistical concepts.
• The instructor’s explanation is good.

Cons-

• Some concepts are not understandable by beginners.

You Should Enroll if-

• You want to learn the basics.

Interested to Enroll?

If yes, then start learning- Statistics literacy for non-statisticians

9. Statistics and probability– Khan Academy

Rating	NA
Time to Complete-	Less than a month
Best For-	Beginner

This “Statistics and probability” course covers basic probability and distributions to more advanced concepts like inference or ANOVA models. This course is the best step after going through an Introductory Statistics book like Bayesian Statistics the Fun Way, which is more theoretical and has less code.

Most of the Khan Academy courses are combined with fun and short videos with quizzes. In quizzes you get points. These quizzes will help you to check your statistical knowledge level. There is one “Course Challenge” in this course, where are 30 problems and you have to answer these problems.

Pros-

• The course is combined with quizzes.

Cons-

• Not good for beginners.

You Should Enroll if-

• You have some basic understanding of maths.

Interested to Enroll?

If yes, then start learning- Statistics and probability

That’s all!

These are the 9 Best Free Online Courses for Statistics.

Comparison of Free Statistics Courses

S/N	Course Name	Rating	Best For	Time to Complete
1.	Intro to Statistics– Udacity	NA	Beginners	2 Months
2.	Introduction to Statistics– Coursera	4.5/5	Beginners	15 hours
3.	Intro to Descriptive Statistics– Udacity	NA	Beginners	2 Months
4.	Intro to Inferential Statistics– Udacity	NA	Intermediate	2 Months
5.	Bayesian Statistics: From Concept to Data Analysis– Coursera	4.6/5	Intermediate	12 hours
6.	Introduction to Bayesian Statistics– Udemy	4.8/5	Beginner	1hr 19min
7.	Python and Statistics for Financial Analysis– Coursera	4.4/5	Intermediate	13 hours
8.	Statistics literacy for non-statisticians– Udemy	4.7/5	Beginner	1hr 36min
9.	Statistics and probability– Khan Academy	NA	Beginner	Less than a month

My Recommendation

I would recommend Intro to Statistics by Udacity for beginners. This course will provide a solid understanding of statistics along with practical exercises. For those who already knew some statistical concepts, I would suggest Bayesian Statistics: From Concept to Data Analysis by Coursera. In this course, you will learn R Programming basics too.

Now, it’s time to wrap up.

Conclusion

I hope these 9 Best Free Online Courses for Statistics will help you to learn statistics for data science. My aim is to provide you with the best resources for Learning. If you have any doubt or questions, feel free to ask me in the comment section.

All the Best!

Happy Learning!

Thank YOU!

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Though of the Day…

‘ It’s what you learn after you know it all that counts.’

– John Wooden