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 California, Santa Cruz
Bayesian Statistics: From Concept to Data Analysis
Skills you'll gain: Bayesian Statistics, Statistical Inference, Data Analysis, Probability, Statistical Modeling, Statistical Analysis, Microsoft Excel, Probability Distribution, R Programming, Regression Analysis
4.6
Rating, 4.6 out of 5 stars
3.2K reviews
Intermediate · Course · 1 - 4 Weeks
IBM
IBM Data Warehouse Engineer
Skills you'll gain: Data Warehousing, SQL, Extract, Transform, Load, Apache Airflow, Linux Commands, IBM Cognos Analytics, Data Pipelines, Apache Kafka, Database Management, Bash (Scripting Language), Shell Script, Database Architecture and Administration, Data Visualization, Dashboard, File Management, Star Schema, Stored Procedure, Data Architecture, Unix Shell, Relational Databases
4.7
Rating, 4.7 out of 5 stars
5.9K reviews
Beginner · Professional Certificate · 3 - 6 Months
Google
Foundations: Data, Data, Everywhere
Skills you'll gain: Data Ethics, Data Analysis, Analytics, Data-Driven Decision-Making, Google Sheets, Business Analytics, Spreadsheet Software, Analytical Skills, Data Sharing, Data Cleansing, Data Processing, Data Strategy, Data Visualization Software, SQL
4.8
Rating, 4.8 out of 5 stars
113K reviews
Beginner · Course · 1 - 4 Weeks
Duke University
Introduction to Probability and Data with R
Skills you'll gain: Sampling (Statistics), Exploratory Data Analysis, Statistical Inference, Probability Distribution, Bayesian Statistics, R Programming, Data Analysis, Probability, Statistics, Statistical Analysis, Statistical Software, Data Science, Descriptive Statistics
4.7
Rating, 4.7 out of 5 stars
5.7K reviews
Beginner · Course · 1 - 3 Months
IBM
Exploratory Data Analysis for Machine Learning
Skills you'll gain: Exploratory Data Analysis, Feature Engineering, Data Cleansing, Data Access, Data Analysis, Statistical Inference, Statistical Hypothesis Testing, Data Quality, Probability & Statistics, Jupyter, Big Data, Machine Learning, Data Manipulation, Pandas (Python Package), Statistical Analysis, Data Transformation, Data Presentation, Artificial Intelligence
4.6
Rating, 4.6 out of 5 stars
2.2K reviews
Intermediate · Course · 1 - 3 Months
IBM
IBM Data Analytics with Excel and R
Skills you'll gain: Data Storytelling, Data Presentation, Interactive Data Visualization, Data Visualization Software, Data Visualization, Shiny (R Package), Data Wrangling, Exploratory Data Analysis, Relational Databases, Big Data, Ggplot2, Database Design, Data Analysis, IBM Cognos Analytics, Data Mining, Dashboard, Excel Formulas, Data Manipulation, Web Scraping, Microsoft Excel
Build toward a degree
4.7
Rating, 4.7 out of 5 stars
28K reviews
Beginner · Professional Certificate · 3 - 6 Months
Macquarie University
Excel Skills for Data Analytics and Visualization
Skills you'll gain: Pivot Tables And Charts, Data Storytelling, Data Presentation, Power BI, Excel Formulas, Data Analysis Expressions (DAX), Data Visualization Software, Data Visualization, Interactive Data Visualization, Microsoft Excel, Spreadsheet Software, Dashboard, Data Modeling, Data Cleansing, Data Manipulation, Excel Macros, Infographics, Data Transformation, Data Validation, Data Analysis
4.8
Rating, 4.8 out of 5 stars
5.6K reviews
Intermediate · Specialization · 3 - 6 Months
Macquarie University
Excel Fundamentals for Data Analysis
Skills you'll gain: Excel Formulas, Microsoft Excel, Data Cleansing, Data Manipulation, Data Transformation, Data Validation, Data Analysis, Pivot Tables And Charts, Automation
4.8
Rating, 4.8 out of 5 stars
4K reviews
Intermediate · Course · 1 - 3 Months
Status: Free
Coursera Instructor Network
Data Science for Professionals
Skills you'll gain: Predictive Modeling, Predictive Analytics, Statistical Analysis, Data Manipulation, Data Analysis, Data Science, Pandas (Python Package), Data Visualization Software, Statistics, Data Cleansing, Data Processing, Data-Driven Decision-Making, Business Analytics, Exploratory Data Analysis, Machine Learning
4.5
Rating, 4.5 out of 5 stars
13 reviews
Beginner · Course · 1 - 4 Weeks
University of Pennsylvania
Data Analysis Using Python
Skills you'll gain: Matplotlib, Data Analysis, Pandas (Python Package), Data Science, Data Cleansing, Pivot Tables And Charts, Data Visualization Software, Data Manipulation, Scatter Plots, NumPy, Data Quality, Jupyter, Data Import/Export, Histogram, Python Programming, Programming Principles
4.5
Rating, 4.5 out of 5 stars
416 reviews
Beginner · Course · 1 - 4 Weeks
Johns Hopkins University
Command Line Tools for Genomic Data Science
Skills you'll gain: Unix Commands, Bioinformatics, Unix Shell, Unix, Data Management, Command-Line Interface, Big Data, Data Manipulation, File Management, Life Sciences
4
Rating, 4 out of 5 stars
560 reviews
Mixed · Course · 1 - 4 Weeks
IBM
IBM AI Foundations for Business
Skills you'll gain: Data Mining, Artificial Intelligence, Generative AI, Data Ethics, Artificial Intelligence and Machine Learning (AI/ML), Big Data, Information Architecture, Strategic Decision-Making, Cloud Computing, Data Analysis, Data Science, Deep Learning, Digital Transformation, Data Strategy, Data-Driven Decision-Making, Artificial Neural Networks, Business Strategy, Business Process Automation, Technology Strategies, Governance
4.7
Rating, 4.7 out of 5 stars
92K reviews
Beginner · Specialization · 1 - 3 Months