This Statistics for Data Science course is designed to introduce you to the basic principles of statistical methods and procedures used for data analysis. After completing this course you will have practical knowledge of crucial topics in statistics including - data gathering, summarizing data using descriptive statistics, displaying and visualizing data, examining relationships between variables, probability distributions, expected values, hypothesis testing, introduction to ANOVA (analysis of variance), regression and correlation analysis. You will take a hands-on approach to statistical analysis using Python and Jupyter Notebooks – the tools of choice for Data Scientists and Data Analysts.
Statistics for Data Science with Python
Statistics for Data Science with Python
This course is part of Data Science Fundamentals with Python and SQL Specialization
Instructors: Murtaza Haider
35,587 already enrolled
Included with 
Gain insight into a topic and learn the fundamentals.
4.5
(415 reviews)
14 hours to complete
3 weeks at 4 hours a week
Flexible schedule
Learn at your own pace
91%
Most learners liked this course
What you'll learn
Write Python code to conduct various statistical tests including a T test, an ANOVA, and regression analysis.
Interpret the results of your statistical analysis after conducting hypothesis testing.
Calculate descriptive statistics and visualization by writing Python code.
Create a final project that demonstrates your understanding of various statistical test using Python and evaluate your peer's projects.
Skills you'll gain
Details to know
Shareable certificate
Add to your LinkedIn profile
Assessments
6 quizzes, 6 assignments
Taught in English
See how employees at top companies are mastering in-demand skills
Build your subject-matter expertise
This course is part of the Data Science Fundamentals with Python and SQL Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV
Share it on social media and in your performance review
There are 9 modules in this course
Welcome!
What's included
2 videos2 readings1 app item
This module will focus on introducing the basics of descriptive statistics - mean, median, mode, variance, and standard deviation. It will explain the usefulness of the measures of central tendency and dispersion for different levels of measurement.
What's included
4 videos2 quizzes1 app item
This module will focus on different types of visualization depending on the type of data and information we are trying to communicate. You will learn to calculate and interpret these measures and graphs.
What's included
4 videos2 quizzes1 app item
This module will introduce the basic concepts and application of probability and probability distributions.
What's included
5 videos2 readings2 quizzes1 app item
This module will focus on teaching the appropriate test to use when dealing with data and relationships between them. It will explain the assumptions of each test and the appropriate language when interpreting the results of a hypothesis test.
What's included
5 videos2 assignments1 app item
This module will dive straight into using python to run regression analysis for testing relationships and differences in sample and population means rather than the classical hypothesis testing and how to interpret them.
What's included
4 videos2 assignments1 app item
In the final week of the course, you will be given a dataset and a scenario where you will use descriptive statistics and hypothesis testing to give some insights about the data you were provided. You will use Watson studio for your analysis and upload your notebook for a peer review and will also review a peer's project. The readings in this module contain the complete information you need.
What's included
8 readings1 peer review2 app items
What's included
1 assignment
Cheat sheet for Statistics in Python
What's included
1 reading1 assignment1 plugin
Instructors
Instructor ratings
4.4 (155 ratings)Offered by
Recommended if you're interested in Probability and Statistics
University of Illinois Urbana-Champaign
CertNexus
Johns Hopkins University
University of Michigan
Why people choose Coursera for their career
Felipe M.
Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
Jennifer J.
Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
Larry W.
Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
Chaitanya A.
"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."
Learner reviews
4.5
415 reviews
- 5 stars
70.19%
- 4 stars
19.23%
- 3 stars
5.28%
- 2 stars
2.16%
- 1 star
3.12%
Showing 3 of 415
MC
5
Reviewed on Nov 30, 2021
Excellent Course! Clear and didactical explanations, objectives exercices and very oriented subjects! For those who are interested in data analytics, this the trainning you should take!
AY
5
Reviewed on Jan 12, 2021
One of the best course I have taken online. Way of teaching was outstanding.
HD
5
Reviewed on Jan 13, 2021
A well structured course, simple and direct to the point, with a little of exercising you'll come out with a huge understanding of the statistical concepts.
New to Probability and Statistics? Start here.
Open new doors with Coursera Plus
Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Advance your career with an online degree
Earn a degree from world-class universities - 100% online
Join over 3,400 global companies that choose Coursera for Business
Upskill your employees to excel in the digital economy
Frequently asked questions
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.