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 Analysis with Python
Skills you'll gain: Data Wrangling, Data Cleansing, Data Analysis, Data Manipulation, Data Import/Export, Exploratory Data Analysis, Predictive Analytics, Data Science, Statistical Analysis, Regression Analysis, Predictive Modeling, Pandas (Python Package), Analytics, Scikit Learn (Machine Learning Library), Data-Driven Decision-Making, Machine Learning Methods, Feature Engineering, Statistical Methods, Python Programming, NumPy
4.7
Rating, 4.7 out of 5 stars
19K reviews
Intermediate · Course · 1 - 3 Months
IBM
Python for Data Science, AI & Development
Skills you'll gain: Jupyter, Automation, Web Scraping, Python Programming, Data Manipulation, Data Import/Export, Scripting, Data Structures, Data Processing, Data Collection, Application Programming Interface (API), Pandas (Python Package), Programming Principles, NumPy, Object Oriented Programming (OOP), Computer Programming
4.6
Rating, 4.6 out of 5 stars
41K reviews
Beginner · Course · 1 - 3 Months
IBM
Excel Basics for Data Analysis
Skills you'll gain: Excel Formulas, Microsoft Excel, Data Cleansing, Data Analysis, Data Import/Export, Spreadsheet Software, Data Quality, Pivot Tables And Charts, Google Sheets, Data Entry, Data Manipulation, Information Privacy
4.8
Rating, 4.8 out of 5 stars
9.5K reviews
Beginner · Course · 1 - 3 Months
IBM
Python Project for Data Science
Skills you'll gain: Dashboard, Pandas (Python Package), Data Visualization Software, Web Scraping, Jupyter, Data Analysis, Data Wrangling, Data Science, Data Processing, NumPy, Data Manipulation, Python Programming, Data Collection
4.5
Rating, 4.5 out of 5 stars
4.6K reviews
Intermediate · Course · 1 - 4 Weeks
Google
Data Analysis with R Programming
Skills you'll gain: Rmarkdown, Ggplot2, R Programming, Data Analysis, Tidyverse (R Package), Data Visualization Software, Data Cleansing, Statistical Analysis, Data Manipulation, Package and Software Management, Data Structures
4.8
Rating, 4.8 out of 5 stars
11K reviews
Beginner · Course · 1 - 3 Months
University of Michigan
Python for Everybody
Skills you'll gain: Web Scraping, Data Processing, Relational Databases, JSON, Database Design, SQL, Network Protocols, Databases, Web Services, Restful API, Programming Principles, Data Cleansing, Data Structures, Data Storytelling, Data Collection, Computer Programming, Python Programming, Data Manipulation, Development Environment, Computational Thinking
Build toward a degree
4.8
Rating, 4.8 out of 5 stars
277K reviews
Beginner · Specialization · 3 - 6 Months
IBM
Applied Data Science
Skills you'll gain: Dashboard, Data Visualization Software, Plotly, Data Wrangling, Data Visualization, Interactive Data Visualization, Statistical Reporting, Exploratory Data Analysis, Data Cleansing, Jupyter, Matplotlib, Data Analysis, Pandas (Python Package), Data Manipulation, Seaborn, Data Import/Export, Predictive Modeling, Web Scraping, Automation, Python Programming
Build toward a degree
4.6
Rating, 4.6 out of 5 stars
58K reviews
Beginner · Specialization · 3 - 6 Months
University of California, Davis
Learn SQL Basics for Data Science
Skills you'll gain: Data Governance, Presentations, Data Cleansing, Feature Engineering, SQL, Apache Spark, A/B Testing, Distributed Computing, Descriptive Statistics, Data Lakes, Data Quality, Data Storytelling, Data Analysis, Peer Review, Exploratory Data Analysis, Data Pipelines, Databricks, JSON, Query Languages, Data Manipulation
4.6
Rating, 4.6 out of 5 stars
18K reviews
Beginner · Specialization · 3 - 6 Months
Johns Hopkins University
Genomic Data Science
Skills you'll gain: Bioinformatics, Unix Commands, Biostatistics, Exploratory Data Analysis, Statistical Analysis, Unix, Data Science, Data Management, Statistical Methods, Command-Line Interface, Statistical Hypothesis Testing, Linux Commands, Science and Research, Statistical Modeling, Data Structures, Data Analysis, Big Data, R Programming, Computational Thinking, Jupyter
4.5
Rating, 4.5 out of 5 stars
6.6K reviews
Intermediate · Specialization · 3 - 6 Months
IBM
Tools for Data Science
Skills you'll gain: Jupyter, Data Visualization Software, Data Science, GitHub, Big Data, R Programming, Statistical Programming, Application Programming Interface (API), Machine Learning, Cloud Computing, Git (Version Control System), Python Programming, SQL
4.5
Rating, 4.5 out of 5 stars
30K reviews
Beginner · Course · 1 - 3 Months
IBM
Data Science Methodology
Skills you'll gain: Jupyter, Peer Review, Data Modeling, Data Science, Data Cleansing, Business Analysis, Data Processing, Predictive Modeling, Data Quality, Data Storytelling, User Feedback, Decision Tree Learning
4.6
Rating, 4.6 out of 5 stars
21K reviews
Beginner · Course · 1 - 4 Weeks
Google
Foundations of Data Science
Skills you'll gain: Data Storytelling, Data Ethics, Data Analysis, Workflow Management, Data-Driven Decision-Making, Analytical Skills, Data Science, Technical Communication, Communication, Business, Business Workflow Analysis, Project Management, Stakeholder Communications, Professional Networking
4.7
Rating, 4.7 out of 5 stars
3.1K reviews
Advanced · Course · 1 - 3 Months