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 .

Top Statistics For Data Science Courses - Learn Statistics For Data Science Online

Explore the Statistics for Data Science Course Catalog

University of Amsterdam
Basic Statistics
Skills you'll gain: Descriptive Statistics, Statistical Hypothesis Testing, Statistical Software, Probability Distribution, Sampling (Statistics), Correlation Analysis, Probability, Sample Size Determination, Statistics, Regression Analysis, Statistical Inference
4.6
Rating, 4.6 out of 5 stars
4.5K reviews
Beginner · Course · 1 - 3 Months
University of Pennsylvania
Statistics for Data Science Essentials
Skills you'll gain: Probability, Probability & Statistics, Sampling (Statistics), Probability Distribution, Statistics, Data Science, Statistical Inference, Descriptive Statistics, Statistical Analysis, General Mathematics
4.7
Rating, 4.7 out of 5 stars
6 reviews
Intermediate · Course · 1 - 4 Weeks
Johns Hopkins University
Data Science: Statistics and Machine Learning
Skills you'll gain: Shiny (R Package), Rmarkdown, Regression Analysis, Leaflet (Software), Exploratory Data Analysis, Statistical Inference, Predictive Modeling, Statistical Hypothesis Testing, Plotly, Machine Learning Algorithms, Interactive Data Visualization, Probability & Statistics, Statistical Machine Learning, Feature Engineering, Statistical Analysis, Statistical Modeling, Probability, Correlation Analysis, Data Science, Data Analysis
4.4
Rating, 4.4 out of 5 stars
7.2K reviews
Intermediate · Specialization · 3 - 6 Months
Status: Free
Duke University
Data Science Math Skills
Skills you'll gain: Probability, Bayesian Statistics, Calculus, Graphing, Data Science, Algebra, Arithmetic, Derivatives
4.5
Rating, 4.5 out of 5 stars
13K reviews
Beginner · Course · 1 - 3 Months
University of Michigan
Inferential Statistical Analysis with Python
Skills you'll gain: Statistical Hypothesis Testing, Statistical Inference, Bayesian Statistics, Probability & Statistics, Statistical Analysis, Data Analysis, Sampling (Statistics), Jupyter, Quantitative Research, Python Programming, Matplotlib, NumPy
4.6
Rating, 4.6 out of 5 stars
917 reviews
Intermediate · Course · 1 - 4 Weeks
Multiple educators
Data Science Foundations
Skills you'll gain: Dashboard, Pseudocode, Jupyter, Algorithms, Data Mining, Pandas (Python Package), Data Visualization Software, Correlation Analysis, Web Scraping, NumPy, R Programming, Probability & Statistics, Predictive Modeling, Big Data, Automation, Computer Programming Tools, GitHub, Data Analysis Software, Machine Learning Algorithms, Unsupervised Learning
4.6
Rating, 4.6 out of 5 stars
111K reviews
Beginner · Specialization · 3 - 6 Months
University of Colorado Boulder
Statistical Learning for Data Science
Skills you'll gain: Statistical Modeling, Statistical Machine Learning, Regression Analysis, Statistical Methods, Data Science, Predictive Modeling, Statistical Analysis, Supervised Learning, R Programming, Artificial Neural Networks, Dimensionality Reduction, Unsupervised Learning, Classification And Regression Tree (CART), Probability & Statistics, Advanced Analytics, Decision Tree Learning, Machine Learning, Sampling (Statistics), Feature Engineering, Machine Learning Algorithms
Build toward a degree
4
Rating, 4 out of 5 stars
17 reviews
Intermediate · Specialization · 3 - 6 Months
Status: [object Object]
Google
Google Data Analytics
Skills you'll gain: Data Storytelling, Rmarkdown, Data Visualization, Data Presentation, Data Ethics, Interactive Data Visualization, Interviewing Skills, Data Cleansing, 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
164K reviews
Beginner · Professional Certificate · 3 - 6 Months
IBM
Data Science Fundamentals with Python and SQL
Skills you'll gain: Dashboard, SQL, Descriptive Statistics, Jupyter, Statistical Analysis, Data Analysis, Probability Distribution, Pandas (Python Package), Data Visualization Software, Statistics, Data Visualization, Databases, Stored Procedure, Web Scraping, Relational Databases, R Programming, Automation, Computer Programming Tools, GitHub, Python Programming
Build toward a degree
4.6
Rating, 4.6 out of 5 stars
70K reviews
Beginner · Specialization · 3 - 6 Months
Johns Hopkins University
Data Science: Foundations using R
Skills you'll gain: Rmarkdown, Exploratory Data Analysis, Version Control, Statistical Analysis, R Programming, Data Manipulation, Data Cleansing, Data Science, Data Visualization, Statistical Programming, Ggplot2, Dimensionality Reduction, Data Visualization Software, Data Integration, Knitr, Data Analysis, Data Import/Export, General Science and Research, Data Sharing, Statistical Reporting
4.6
Rating, 4.6 out of 5 stars
48K reviews
Beginner · Specialization · 3 - 6 Months
Google
Google Advanced Data Analytics
Skills you'll gain: Exploratory Data Analysis, Data Storytelling, Sampling (Statistics), Data Ethics, Data Visualization Software, Data Presentation, Statistical Hypothesis Testing, Regression Analysis, Feature Engineering, Data Transformation, Data Visualization, Probability & Statistics, Tableau Software, Data Manipulation, Advanced Analytics, Data Cleansing, Object Oriented Programming (OOP), Applied Machine Learning, Statistical Analysis, Jupyter
Build toward a degree
4.7
Rating, 4.7 out of 5 stars
5.7K reviews
Advanced · Professional Certificate · 3 - 6 Months
Status: Free
University of Leeds
Programming for Data Science
Skills you'll gain: Jupyter, Programming Principles, Computer Programming, Python Programming, Development Environment, Scripting, Data Structures, Data Manipulation, Debugging
4.3
Rating, 4.3 out of 5 stars
23 reviews
Beginner · Course · 1 - 4 Weeks