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

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
Johns Hopkins University
A Crash Course in Data Science
Skills you'll gain: Data Science, Data Analysis, Data-Driven Decision-Making, Project Design, Performance Metric, Software Engineering, Machine Learning, Statistical Inference
4.5
Rating, 4.5 out of 5 stars
8.2K reviews
Beginner · Course · 1 - 4 Weeks
University of Colorado Boulder
Statistics and Data Analysis with Excel, Part 1
Skills you'll gain: Descriptive Statistics, Statistical Visualization, Data Transformation, Data Cleansing, Probability, Box Plots, Histogram, Probability Distribution, Probability & Statistics, Scatter Plots, Statistics, Descriptive Analytics, Microsoft Excel, Excel Formulas, Data Analysis, Spreadsheet Software, Bayesian Statistics
4.7
Rating, 4.7 out of 5 stars
27 reviews
Beginner · Course · 1 - 3 Months
Johns Hopkins University
Statistical Inference
Skills you'll gain: Statistical Inference, Statistical Hypothesis Testing, Probability & Statistics, Probability, Statistics, Bayesian Statistics, Statistical Methods, Statistical Modeling, Statistical Analysis, Probability Distribution, Sampling (Statistics)
4.2
Rating, 4.2 out of 5 stars
4.4K reviews
Mixed · Course · 1 - 4 Weeks
Meta
Statistics Foundations
Skills you'll gain: Bayesian Statistics, Descriptive Statistics, Statistical Hypothesis Testing, Statistical Inference, Sampling (Statistics), Data Modeling, Statistics, Probability & Statistics, Statistical Analysis, Statistical Methods, Statistical Modeling, Marketing Analytics, Tableau Software, Data Analysis, Spreadsheet Software, Quantitative Research, Analytics, Descriptive Analytics, Time Series Analysis and Forecasting, Regression Analysis
4.7
Rating, 4.7 out of 5 stars
322 reviews
Beginner · Course · 1 - 3 Months
Fractal Analytics
Python for Data Science
Skills you'll gain: Exploratory Data Analysis, Feature Engineering, Data Visualization, Statistical Analysis, Probability & Statistics, Pandas (Python Package), Data Analysis, Jupyter, Data Processing, Data Manipulation, Data Science, Descriptive Statistics, Data Transformation, Data Cleansing, Python Programming, Matplotlib
4.1
Rating, 4.1 out of 5 stars
44 reviews
Beginner · Course · 1 - 3 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, Scripting Languages, Data Manipulation
4.3
Rating, 4.3 out of 5 stars
25 reviews
Beginner · Course · 1 - 4 Weeks
Status: Free
Eindhoven University of Technology
Improving your statistical inferences
Skills you'll gain: Statistical Inference, Statistical Hypothesis Testing, Quantitative Research, Bayesian Statistics, Statistical Analysis, Sample Size Determination, Data Analysis, Research, Research Design, Research Methodologies, Data Sharing, Probability
4.9
Rating, 4.9 out of 5 stars
792 reviews
Intermediate · Course · 1 - 3 Months
Status: Free
University of London
Probability and Statistics: To p or not to p?
Skills you'll gain: Descriptive Statistics, Probability & Statistics, Statistical Methods, Statistical Hypothesis Testing, Data-Driven Decision-Making, Statistical Modeling, Data Analysis, Probability, Statistical Visualization, Probability Distribution, Statistical Analysis, Data Presentation, Sampling (Statistics), Statistical Inference, Mathematical Modeling, Decision Tree Learning, Applied Mathematics
4.6
Rating, 4.6 out of 5 stars
1.5K reviews
Beginner · Course · 1 - 3 Months
Status: Free
University of London
Foundations of Data Science: K-Means Clustering in Python
Skills you'll gain: Matplotlib, Probability & Statistics, Scatter Plots, Data Science, Unsupervised Learning, Statistics, NumPy, Python Programming, Pandas (Python Package), Data Analysis, Machine Learning Algorithms, Descriptive Statistics, Data Manipulation
4.6
Rating, 4.6 out of 5 stars
716 reviews
Beginner · Course · 1 - 3 Months
Status: AI skills
Microsoft
Microsoft Power BI Data Analyst
Skills you'll gain: Data Storytelling, Dashboard, Excel Formulas, Extract, Transform, Load, Power BI, Data Analysis Expressions (DAX), Microsoft Excel, Data Modeling, Data-Driven Decision-Making, Star Schema, Data Analysis, Data Presentation, Data Visualization Software, Microsoft Power Platform, Data Integrity, Spreadsheet Software, Data Validation, Data Transformation, Data Cleansing, Data Visualization
Build toward a degree
4.6
Rating, 4.6 out of 5 stars
7K reviews
Beginner · Professional Certificate · 3 - 6 Months
IBM
Data Analysis with Python
Skills you'll gain: Data Wrangling, Data Cleansing, Data Analysis, Data Manipulation, Data Import/Export, Exploratory Data Analysis, Statistical Analysis, Regression Analysis, Predictive Modeling, Pandas (Python Package), Scikit Learn (Machine Learning Library), Data-Driven Decision-Making, Statistical Modeling, Machine Learning Methods, Feature Engineering, Python Programming, NumPy
4.7
Rating, 4.7 out of 5 stars
19K reviews
Intermediate · Course · 1 - 3 Months