What is statistics for data science?

Statistics for data science refers to the mathematical analysis used to sort, analyze, interpret, and present data. It includes concepts like probability distribution, regression, and over or under-sampling. Descriptive statistics organizes data based on characteristics of the data set, such as normal distribution, central tendency, variability, and standard deviation. Inferential statistics incorporates the use of probability theory to infer characteristics of the data set.

Why learn statistics for data science?

Learning statistics for data science can lead to career opportunities in data science and related fields. As organizations increasingly rely on data to make decisions, they tend to seek out analysts who understand how to work with data and present it to stakeholders. Learning statistics for data science can also provide a good salary. As of 2020, the median pay for computer and information research scientists in the US is $122,840 and the job market remains positive, according to the Bureau of Labor Statistics. Mathematicians and statisticians have a similar job outlook and a median salary of $92,030 per year.

What are typical careers that use statistics for data science?

Data analysis, data architects, data scientists, and information officers typically use statistics for data science in their regular work. Data science is a broad field, and statistics can be useful in other roles that require analyzing and presenting data. This includes data warehouse analysts, data visualization developers, database managers, and machine learning engineers. Additional related fields include financial analysts, teachers, and researchers working for universities and corporate settings.

How can online courses help me learn statistics for data science?

Through online courses, you can learn the fundamentals of statistics for data science, including the theories and techniques statisticians use in their work. Some courses explore fundamental concepts like Bayes’ Theorem and probability theory. Others present methods for calculating and evaluating data sets. You can brush up on your knowledge of programs statisticians use, like Excel and Python, or examine the application of statistics specific fields.

What are the benefits of taking an online Statistics for Data Science course?

Online Statistics for Data Science courses offer a convenient and flexible way to enhance your knowledge or learn new Statistics for Data Science skills. Choose from a wide range of Statistics for Data Science courses offered by top universities and industry leaders tailored to various skill levels.

What Statistics for Data Science courses are best for training and upskilling employees or the workforce?

When looking to enhance your workforce's skills in Statistics for Data Science, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here .

Best Statistics for Data Science Courses & Certificates [2025]

Explore the Statistics for Data Science Course Catalog

Johns Hopkins University
Advanced Statistics for Data Science
Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Regression Analysis, Bayesian Statistics, Statistical Analysis, Probability & Statistics, Statistical Inference, Statistical Methods, Statistical Modeling, Linear Algebra, Probability, R Programming, Biostatistics, Data Analysis, Data Science, Probability Distribution, Mathematical Modeling, Data Modeling, Applied Mathematics, Predictive Modeling
4.4
Rating, 4.4 out of 5 stars
759 reviews
Advanced · Specialization · 3 - 6 Months
IBM
Statistics for Data Science with Python
Skills you'll gain: Descriptive Statistics, Statistical Analysis, Data Analysis, Probability Distribution, Statistics, Data Visualization, Statistical Hypothesis Testing, Regression Analysis, Data Science, Matplotlib, Exploratory Data Analysis, Statistical Inference, Probability, Correlation Analysis, Pandas (Python Package), Jupyter
4.5
Rating, 4.5 out of 5 stars
431 reviews
Mixed · Course · 1 - 3 Months
University of Michigan
Statistics with Python
Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Statistical Modeling, Statistical Inference, Statistical Methods, Bayesian Statistics, Data Visualization, Statistics, Matplotlib, Statistical Visualization, Statistical Software, Probability & Statistics, Statistical Analysis, Jupyter, Statistical Programming, Regression Analysis, Data Visualization Software, Predictive Modeling, Exploratory Data Analysis, Data Analysis
4.6
Rating, 4.6 out of 5 stars
3.3K reviews
Beginner · Specialization · 1 - 3 Months
Google
The Power of Statistics
Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Descriptive Statistics, Data Analysis, Statistical Analysis, Probability Distribution, Statistical Methods, Statistics, Statistical Inference, Probability, Bayesian Statistics, Statistical Programming, A/B Testing
4.8
Rating, 4.8 out of 5 stars
760 reviews
Advanced · Course · 1 - 3 Months
DeepLearning.AI
Probability & Statistics for Machine Learning & Data Science
Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Probability, Statistical Inference, A/B Testing, Statistical Analysis, Data Science, Exploratory Data Analysis, Data Analysis, Statistical Visualization
4.6
Rating, 4.6 out of 5 stars
544 reviews
Intermediate · Course · 1 - 4 Weeks
Status: Free
Stanford University
Introduction to Statistics
Skills you'll gain: Descriptive Statistics, Statistics, Statistical Methods, Sampling (Statistics), Statistical Analysis, Data Analysis, Statistical Hypothesis Testing, Regression Analysis, Statistical Inference, Probability, Exploratory Data Analysis, Quantitative Research, Probability Distribution, Correlation Analysis
4.6
Rating, 4.6 out of 5 stars
4K reviews
Beginner · Course · 1 - 3 Months
Status: AI skills
IBM
IBM Data Science
Skills you'll gain: Dashboard, Data Visualization Software, Data Wrangling, Data Visualization, SQL, Supervised Learning, Feature Engineering, Plotly, Interactive Data Visualization, Jupyter, Statistical Reporting, Exploratory Data Analysis, Data Mining, Data Cleansing, Matplotlib, Data Analysis, Unsupervised Learning, Generative AI, Pandas (Python Package), Professional Networking
Build toward a degree
4.6
Rating, 4.6 out of 5 stars
141K reviews
Beginner · Professional Certificate · 3 - 6 Months
DeepLearning.AI
Mathematics for Machine Learning and Data Science
Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Probability, Linear Algebra, Statistical Inference, A/B Testing, Statistical Analysis, Applied Mathematics, NumPy, Calculus, Dimensionality Reduction, Machine Learning, Jupyter, Python Programming, Data Manipulation, Data Science
4.6
Rating, 4.6 out of 5 stars
2.7K reviews
Intermediate · Specialization · 1 - 3 Months
Status: New AI skills
Google
Google Data Analytics
Skills you'll gain: Data Storytelling, Data Visualization, Data Presentation, Data Ethics, Rmarkdown, Interactive Data Visualization, Data Cleansing, Interviewing Skills, Data Validation, Ggplot2, Tableau Software, Presentations, Spreadsheet Software, Data Analysis, Data Visualization Software, Stakeholder Communications, Dashboard, Sampling (Statistics), Analytics, Stakeholder Management
Build toward a degree
4.8
Rating, 4.8 out of 5 stars
166K reviews
Beginner · Professional Certificate · 3 - 6 Months
IBM
Databases and SQL for Data Science with Python
Skills you'll gain: SQL, Relational Databases, Databases, Stored Procedure, Database Management, Database Design, Query Languages, Data Manipulation, Jupyter, Data Analysis, Pandas (Python Package), Transaction Processing
4.7
Rating, 4.7 out of 5 stars
22K reviews
Beginner · Course · 1 - 3 Months
IBM
Introduction to Data Analytics
Skills you'll gain: Big Data, Data Analysis, Statistical Analysis, Apache Hadoop, Apache Hive, Data Collection, Data Mart, Data Warehousing, Data Storytelling, Apache Spark, Data Cleansing, Data Lakes, Data Visualization Software, SQL
4.8
Rating, 4.8 out of 5 stars
18K reviews
Beginner · Course · 1 - 3 Months
Coursera Project Network
Statistics For Data Science
Skills you'll gain: Correlation Analysis, Probability & Statistics, Statistics, Statistical Analysis, Data Analysis, Sampling (Statistics), Data Science, Probability Distribution, Descriptive Statistics, Statistical Inference, Exploratory Data Analysis
3.9
Rating, 3.9 out of 5 stars
32 reviews
Beginner · Guided Project · Less Than 2 Hours