**Coursera** is an **E-Learning platform **that provides thousands of online courses on various subjects. And **Coursera** has a wide range of **Statistics** courses too. That’s why I thought to share the **10** **Best Statistics Courses on Coursera **with you. So, give your few minutes to this article and find out the **Best Statistics Courses on Coursera**.

Now, without any further ado, let’s get started-

**Best Statistics Courses on Coursera **

- 1. Statistics with R Specialization– Duke University
- 2. Introduction to Statistics- Standford University
- 3. Statistics with Python Specialization-University of Michigan
- 4. Data Science: Statistics and Machine Learning Specialization– Johns Hopkins University
- 5. Basic Statistics– University of Amsterdam
- 6. Business Statistics and Analysis Specialization– Rice University
- 7. Statistical Analysis with R for Public Health Specialization– Imperial College London
- 8. Bayesian Statistics: From Concept to Data Analysis- University of California, Santa Cruz
- 9. Python and Statistics for Financial Analysis- The Hong Kong University of Science and Technology
- 10. Advanced Statistics for Data Science Specialization- Johns Hopkins University

**1. ****Statistics with R Specialization**– **Duke University**

**–**

**Statistics with R Specialization**

**Duke University****Rating-** 4.6/5

**Time to Complete-** 7 months (If you spend 3 hours/week)

This is a **specialization program** available on Coursera. This specialization program will give you **in-depth Statistics knowledge** by using **R Programming**. In this program, you will learn how to **analyze and visualize data in R** and **create reproducible data analysis reports**.

At the beginning of this program, you will learn the **basic probability theory and Bayes’ rule** and examine various types of **sampling methods**, and discuss how such methods can impact the scope of inference.

Then you will learn commonly used **statistical inference methods** for numerical and categorical data and **simple and multiple linear regression models**.

At the end of this course, you will learn **Bayesian Statistics **and learn to use** Bayes’ rule** to transform **prior probabilities into posterior probabilities.** There is a **Capstone Project **at the end of the program.

The capstone project will be an **analysis using R** that answers a specific scientific/business question provided by the course team.

So, if you want to master **Statistics with R programming**, then I would recommend this specialization program. This specialization program contains **5 Courses**. Now, let’s see the details of the courses-

**Courses Include-**

**Introduction to Probability and Data with R****Inferential Statistics****Linear Regression and Modeling****Bayesian Statistics****Statistics with R Capstone**

**Extra Benefits-**

- You will get a
**Shareable Certificate and Course Certificates**upon completion. - Along with this, you will get
**Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, Graded Programming Assignments.**

**You Should Enroll if-**

- You have
**basic math knowledge**. No previous programming knowledge is required for this course.

**Interested to Enroll?**

If yes, then check out all details here- **Statistics with R Specialization**

**2. **** ****Introduction to Statistics**– *Standford University*

**–**

**Introduction to Statistics***Standford University*

**Rating-** 4.5/5

**Time to Complete-**15 hours

This course is **Free to Audit.** That means you can access the full course material free of cost. But you will **not receive the certificate.**

In this course, you will learn the following topics- **Descriptive Statistics, Sampling and Randomized Controlled Experiments, Probability, Sampling Distributions, and the Central Limit Theorem, Regression, Common Tests of Significance, Resampling, Multiple Comparisons.**

Overall this course is good for clearing the basics.

**You Should Enroll if-**

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

**Interested to Enroll?**

If yes, then start learning- **Introduction to Statistics**

**3. ****Statistics with Python Specialization**–**University of Michigan**

**–**

**Statistics with Python Specialization****University of Michigan**

**Rating- **4.5/5

**Time to Complete-** 3 months (If you spend 5 hours/week)

This specialization program is especially dedicated to statistics. In this program, you will learn **basic and intermediate** concepts of** statistical analysis using the Python programming** language.

In this program, you will learn the following topics- **where data come from, what types of data can be collected, study data design, data management, and how to effectively carry out data exploration and visualization.**

Along with that, you will work on a variety of **assignments** that will help you to check your knowledge and ability. This specialization program is a** 3-course series**.

**Extra Benefits-**

- You will get a
**Shareable Certificate and Course Certificates**upon completion. - Along with this, you will get
**Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, Graded Programming Assignments.**

**You Should Enroll if-**

- You have Knowledge of
**basic Python and High school-level algebra.**

**Interested to Enroll?**

If yes, then check out all details here- **Statistics with Python Specialization**

**4. ****Data Science: Statistics and Machine Learning Specialization**– **Johns Hopkins University**

**Data Science: Statistics and Machine Learning Specialization**–

**Johns Hopkins University****Rating- **4.6/5

**Time to Complete-** 6 months (If you spend 6 hours/week)

This is another Specialization program dedicated to **statistics** concepts. In this program, you will learn **statistical inference, regression models, machine learning, and the development of data products.**

At the end of this program, you will work on **Capstone Project**, where you will apply the skills learned by building a data product using real-world data. This specialization program uses the **R programming language.**

There are 5 courses in this specialization program.

**Extra Benefits-**

- You will get a
**Shareable Certificate and Course Certificates**upon completion. - Along with that, you will get
**Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, Graded Programming Assignments.**

**You Should Enroll if-**

- You have a good understanding of R programming.

**Interested to Enroll?**

If yes, then check out all details here- **Data Science: Statistics and Machine Learning Specialization**

**5. ****Basic Statistics**– **University of Amsterdam**

**–**

**Basic Statistics**

**University of Amsterdam****Rating- **4.7/5

**Time to Complete-** 26 Hours

This is a **Free to Audit course **on Coursera. That means you can **access the course material free of cost** but for the **certificate, you have to pay.**

In this course, you will learn the basics of statistics like what cases and variables are and how you can compute measures of central tendency (**mean, median, and mode**) and dispersion (**standard deviation and variance**).

Along with that, you will learn the basics of probability- **calculating probabilities, probability distributions, and sampling distributions.** You will also learn **inferential statistics.**

**Extra Benefits-**

- You will get a
**Shareable Certificate and Course Certificates**upon completion. - Along with that, you will get

**You Should Enroll if-**

- You are beginner and want to learn
**basics of statistics**.

**Interested to Enroll?**

If yes, then check out all details here- **Basic Statistics**

**6. ****Business Statistics and Analysis Specialization**– **Rice University**

**–**

**Business Statistics and Analysis Specialization**

**Rice University****Rating-** 4.8/5

**Time to Complete-** 5 months (If you spend 5 hours/week)

This specialization program will teach you** Business Statistics and Analysis.** In this program, you will learn basic **probability concepts**, including measuring and modeling uncertainty, and you’ll use various **data distributions,** along with the** Linear Regression Model,** to analyze and inform business decisions.

This specialization program has 5 courses.

**Courses Include-**

**Introduction to Data Analysis Using Excel****Basic Data Descriptors, Statistical Distributions, and Application to Business Decisions****Business Applications of Hypothesis Testing and Confidence Interval Estimation****Linear Regression for Business Statistics****Business Statistics and Analysis Capstone**

**Extra Benefits-**

- You will get a
**Shareable Certificate and Course Certificates**upon completion. - Along with that, you will get

**You Should Enroll, If-**

- There is
**no condition for enrolling**in this program. Anyone can enroll in this specialization program. No prior experience is required to enroll in this program.

**Interested to Enroll?**

If yes, then check out all details here- **Business Statistics and Analysis Specialization**

**7. ****Statistical Analysis with R for Public Health Specialization**– **Imperial College London**

**–**

**Statistical Analysis with R for Public Health Specialization**

**Imperial College London****Rating- **4.7/5

**Time to Complete-** 4 months (If you spend 3 hours/week)

This specialization program is especially dedicated to the **Statistical Analysis for Public Health.** In this program, you will learn key statistical concepts like **sampling, uncertainty, variation, missing values, and distributions.**

Along with that, you will get your hands dirty with analyzing data sets covering some big public health challenges – **fruit and vegetable consumption and cancer, risk factors for diabetes, and predictors of death following heart failure hospitalization – using R**.

This specialization consists of 4 courses.

**Extra Benefits-**

- You will get a
**Shareable Certificate and Course Certificates**upon completion. - Along with that, you will get

**You Should Enroll, If-**

- Anyone can enroll who has
**an interest in medicine and statistics**. This is a**Beginner Level**program.**No medical, statistical, or R knowledge is assumed.**

**Interested to Enroll?**

If yes, then check out all details here- **Statistical Analysis with R for Public Health Specialization**

**8. ****Bayesian Statistics: From Concept to Data Analysis**– *University of California, Santa Cruz*

**Bayesian Statistics: From Concept to Data Analysis**–

*University of California, Santa Cruz*

**Rating- **4.6/5

**Time to Complete- **12 hours

This is another **Free to Audit **course for statistics. This course begins with the **basics of probability and Bayes’ theorem**. Then covers the **concepts of statistical inference from both frequentist and Bayesian perspectives.**

After that, you will learn **methods for selecting prior distributions and building models for discrete data**. And in the last, this course covers the **conjugate and objective Bayesian analysis for continuous data.**

**You Should Enroll if-**

- You 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**

**9. ****Python and Statistics for Financial Analysis**– *The Hong Kong University of Science and Technology*

**Python and Statistics for Financial Analysis**–

*The Hong Kong University of Science and Technology*

**Rating- **4.4/5

**Time to Complete-** 13 hours

This is the next **Free to Audit **course by Coursera. This course is a combination of **python coding and statistical concepts.** Throughout this course, you will learn to **visualize and Munging Stock Data, Random variables and distribution, Sampling and Inference, and Linear Regression Models for Financial Analysis.**

And you will also build a model using **multiple indices from the global markets and predict the price change of an ETF of S&P500.**

**You Should Enroll if-**

- You have basic knowledge in probability.

**Interested to Enroll?**

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

**10. Advanced Statistics for Data Science Specialization– ***Johns Hopkins University*

*Johns Hopkins University*

**Rating- **4.4/5

**Time to Complete-** 5 months (If you spend 2 hours/week)

In this specialization program, you will learn **Mathematical Statistics** **concepts **specially used in **biostatistics applications.** These concepts are **probability, distribution, and likelihood concepts to hypothesis testing and case-control sampling.**

Then you will learn linear models for data science and explore **least squares from a linear algebraic and mathematical perspective** and **statistical linear models**, including multivariate regression using the **R programming language**.

This specialization program has 4 courses.

**Courses Include-**

**Mathematical Biostatistics Boot Camp 1****Mathematical Biostatistics Boot Camp 2****Advanced Linear Models for Data Science 1: Least Squares****Advanced Linear Models for Data Science 2: Statistical Linear Models**

**Extra Benefits-**

- You will get a
**Shareable Certificate and Course Certificates**upon completion. - Along with that, you will get

**You Should Enroll, If-**

- You have basic understanding of
**calculus and linear algebra.**

**Interested to Enroll?**

If yes, then check out all details here- **Advanced Statistics for Data Science Specialization**

That’s all!

These are the **10 Best Statistics Courses on Coursera**. Now, it’s time to wrap up.

**Conclusion**

I hope these ** Best Statistics Courses on Coursera **will help you to learn

**Statistics**. I aim to provide you with the best resources for Learning. If you have any doubts or questions, feel free to ask me in the comment section.

All the Best!

Happy Learning!

**You May Also Interested In**

**12 Best Data Visualization Courses Online- You Need to Know in 2024****Data Analyst Online Certification to Become a Successful Data Analyst****8 Best Books on Data Science with Python You Must Read in 202414 Best+Free Data Science with Python Courses Online- [Bestseller 2024]**

**10 Best Online Courses for Data Science with R Programming in 2024**

Thank YOU!

**Explore More about Data Science**,** Visit Here**

## Subscribe For More Updates!

[mc4wp_form id=”28437″]

## Though of the Day…

–

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

### Written By Aqsa Zafar

Founder of MLTUT, Machine Learning Ph.D. scholar at Dayananda Sagar University. Research on social media depression detection. Create tutorials on ML and data science for diverse applications. Passionate about sharing knowledge through website and social media.