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

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
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 Literacy
Skills you'll gain: Survey Creation, Data Visualization, Data Analysis, Peer Review, Research Design, Statistics, Probability & Statistics, Data Presentation, Sampling (Statistics), Regression Analysis, Descriptive Statistics, Research, Probability, Quantitative Research, Statistical Hypothesis Testing, Analytics, Report Writing, Research Methodologies, Correlation Analysis, Statistical Inference
4.6
Rating, 4.6 out of 5 stars
246 reviews
Beginner · Specialization · 3 - 6 Months
IBM
Introduction to R Programming for Data Science
Skills you'll gain: Data Manipulation, Web Scraping, R Programming, Data Analysis, Data Science, Data Structures, Data Import/Export, Exploratory Data Analysis, Programming Principles, Computer Programming, Integrated Development Environments
4.5
Rating, 4.5 out of 5 stars
550 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
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
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
Johns Hopkins University
A Crash Course in Data Science
Skills you'll gain: Data Science, Data Analysis, Business Analytics, Data-Driven Decision-Making, Project Design, Performance Metric, Software Engineering, Project Performance, Machine Learning, Statistical Inference
4.5
Rating, 4.5 out of 5 stars
8.2K reviews
Beginner · Course · 1 - 4 Weeks
University of Michigan
Data Science for Health Research
Skills you'll gain: Exploratory Data Analysis, Rmarkdown, Statistical Modeling, Tidyverse (R Package), Statistical Visualization, Data Visualization Software, Regression Analysis, R Programming, Statistical Methods, Ggplot2, Data Wrangling, Statistical Inference, Probability & Statistics, Scatter Plots, Data Manipulation, Predictive Analytics, Predictive Modeling, Correlation Analysis, Histogram, Classification And Regression Tree (CART)
5
Rating, 5 out of 5 stars
9 reviews
Intermediate · Specialization · 1 - 3 Months
Johns Hopkins University
Statistics for Genomic Data Science
Skills you'll gain: Biostatistics, Bioinformatics, Exploratory Data Analysis, Statistical Analysis, Statistical Methods, Statistical Hypothesis Testing, Statistical Modeling, R Programming, Data Analysis, Statistical Inference, Regression Analysis, Scientific Methods, Data Pipelines, Data Transformation, Data Processing, Data Cleansing
4.2
Rating, 4.2 out of 5 stars
371 reviews
Mixed · Course · 1 - 4 Weeks
IBM
What is Data Science?
Skills you'll gain: Data Mining, Big Data, Cloud Computing, Data Analysis, Data Science, Digital Transformation, Data-Driven Decision-Making, Business Logic, Deep Learning, Machine Learning, Artificial Intelligence
4.7
Rating, 4.7 out of 5 stars
75K reviews
Beginner · Course · 1 - 4 Weeks
Johns Hopkins University
The Data Scientist’s Toolbox
Skills you'll gain: Rmarkdown, Version Control, Data Science, General Science and Research, Data Analysis, R Programming, Statistical Programming, Exploratory Data Analysis, Software Installation
4.6
Rating, 4.6 out of 5 stars
34K reviews
Mixed · Course · 1 - 4 Weeks