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
Databases and SQL for Data Science with Python
Skills you'll gain: SQL, Databases, Stored Procedure, Relational Databases, Database Design, Query Languages, Database Management, Data Analysis, Jupyter, Data Manipulation, Pandas (Python Package), Transaction Processing
4.7
Rating, 4.7 out of 5 stars
22K reviews
Beginner · Course · 1 - 3 Months
Johns Hopkins University
Data Science
Skills you'll gain: Shiny (R Package), Rmarkdown, Exploratory Data Analysis, Regression Analysis, Leaflet (Software), Version Control, Statistical Analysis, R Programming, Data Manipulation, Data Cleansing, Data Science, Statistical Inference, Predictive Modeling, Statistical Hypothesis Testing, Data Wrangling, Data Visualization, Plotly, Machine Learning Algorithms, Plot (Graphics), Knitr
4.5
Rating, 4.5 out of 5 stars
51K reviews
Beginner · Specialization · 3 - 6 Months
Status: New AI skills
Google
Google Data Analytics
Skills you'll gain: Data Storytelling, Data Literacy, Data Visualization, Data Presentation, Data Ethics, Rmarkdown, 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), R Programming
Build toward a degree
4.8
Rating, 4.8 out of 5 stars
167K reviews
Beginner · Professional Certificate · 3 - 6 Months
Multiple educators
Data Science Foundations
Skills you'll gain: Dashboard, Pseudocode, Jupyter, Algorithms, Data Literacy, Data Mining, Pandas (Python Package), Data Visualization Software, Correlation Analysis, Web Scraping, NumPy, Probability & Statistics, Predictive Modeling, Big Data, Computer Programming Tools, Automation, Data Analysis Software, Data Collection, Machine Learning Algorithms, Unsupervised Learning
4.6
Rating, 4.6 out of 5 stars
112K reviews
Beginner · Specialization · 3 - 6 Months
University of Amsterdam
Basic Statistics
Skills you'll gain: Descriptive Statistics, Statistical Hypothesis Testing, Sampling (Statistics), Probability Distribution, Correlation Analysis, Probability, Statistical Inference, Regression Analysis, Sample Size Determination, Statistics, Scientific Methods
4.6
Rating, 4.6 out of 5 stars
4.6K reviews
Beginner · Course · 1 - 3 Months
Rice University
Business Statistics and Analysis
Skills you'll gain: Statistical Hypothesis Testing, Microsoft Excel, Pivot Tables And Charts, Regression Analysis, Descriptive Statistics, Probability & Statistics, Graphing, Spreadsheet Software, Probability Distribution, Business Analytics, Statistical Analysis, Statistical Modeling, Excel Formulas, Data Analysis, Data Presentation, Statistics, Business Analysis, Statistical Methods, Sample Size Determination, Statistical Inference
4.7
Rating, 4.7 out of 5 stars
13K 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
7 reviews
Intermediate · Course · 1 - 4 Weeks
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, Statistical Hypothesis Testing, Databases, Stored Procedure, Web Scraping, Relational Databases, Computer Programming Tools, Automation, Data Analysis Software, Python Programming
Build toward a degree
4.6
Rating, 4.6 out of 5 stars
71K reviews
Beginner · Specialization · 3 - 6 Months
IBM
Introduction to Data Analytics
Skills you'll gain: Big Data, Data Analysis, Statistical Analysis, Apache Hadoop, Apache Hive, Data Warehousing, Apache Spark, Data Cleansing, Data Lakes, Data Visualization Software, Relational Databases
4.8
Rating, 4.8 out of 5 stars
19K reviews
Beginner · Course · 1 - 3 Months
Imperial College London
Mathematics for Machine Learning
Skills you'll gain: Linear Algebra, Dimensionality Reduction, NumPy, Regression Analysis, Calculus, Applied Mathematics, Probability & Statistics, Feature Engineering, Jupyter, Advanced Mathematics, Data Science, Statistics, Machine Learning Algorithms, Machine Learning Methods, Statistical Analysis, Artificial Neural Networks, Algorithms, Data Manipulation, Python Programming, Machine Learning
4.6
Rating, 4.6 out of 5 stars
15K 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 Wrangling, Data Visualization, Plot (Graphics), Statistical Programming, Ggplot2, Big Data, Git (Version Control System), Data Integration, Knitr, Data Analysis, 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 Management, Data-Driven Decision-Making, Project Design, Performance Metric, Software Engineering, Machine Learning, Predictive Modeling, Statistical Inference
4.5
Rating, 4.5 out of 5 stars
8.3K reviews
Beginner · Course · 1 - 4 Weeks