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

Status: Free Trial
IBM
Statistics for Data Science with Python
Skills you'll gain: Statistical Hypothesis Testing, Statistical Analysis, Descriptive Statistics, Data Visualization, Statistical Methods, Probability Distribution, Probability & Statistics, Statistics, Regression Analysis, Plot (Graphics), Matplotlib, Data Analysis, Data Science, Pandas (Python Package), Probability, Correlation Analysis, Jupyter, Histogram
4.5
Rating, 4.5 out of 5 stars
442 reviews
Mixed · Course · 1 - 3 Months
Status: Free Trial
Johns Hopkins University
Advanced Statistics for Data Science
Skills you'll gain: Data Visualization, Probability & Statistics, Statistical Hypothesis Testing, Data Analysis, Bayesian Statistics, Statistics, Biostatistics, Linear Algebra, Statistical Analysis, Data Science, Statistical Methods, Regression Analysis, Probability, Statistical Inference, Sampling (Statistics), Statistical Modeling, Probability Distribution, R Programming, Mathematical Modeling, Sample Size Determination
4.4
Rating, 4.4 out of 5 stars
764 reviews
Advanced · Specialization · 3 - 6 Months
Status: Preview
Stanford University
Introduction to Statistics
Skills you'll gain: Statistics, Descriptive Statistics, Probability & Statistics, Statistical Analysis, Data Analysis, Statistical Methods, Statistical Modeling, Statistical Inference, Sampling (Statistics), Statistical Hypothesis Testing, Data Science, Regression Analysis, Exploratory Data Analysis, Probability, Probability Distribution
4.6
Rating, 4.6 out of 5 stars
4.2K reviews
Beginner · Course · 1 - 3 Months
Status: Free Trial
DeepLearning.AI
Probability & Statistics for Machine Learning & Data Science
Skills you'll gain: Descriptive Statistics, Statistical Hypothesis Testing, Bayesian Statistics, Probability Distribution, Probability & Statistics, Sampling (Statistics), Probability, A/B Testing, Statistics, Data Science, Statistical Analysis, Statistical Inference
4.6
Rating, 4.6 out of 5 stars
588 reviews
Intermediate · Course · 1 - 4 Weeks
Status: Free Trial
Google
The Power of Statistics
Skills you'll gain: Sampling (Statistics), Statistical Analysis, Statistics, Statistical Hypothesis Testing, Data Analysis, Statistical Programming, Statistical Inference, Descriptive Statistics, Probability Distribution, Data Science, Probability, Jupyter, Python Programming
4.8
Rating, 4.8 out of 5 stars
815 reviews
Advanced · Course · 1 - 3 Months
Status: Free Trial
University of Michigan
Statistics with Python
Skills you'll gain: Sampling (Statistics), Statistical Methods, Bayesian Statistics, Data Visualization, Data Analysis, Statistical Modeling, Descriptive Statistics, Statistical Inference, Regression Analysis, Exploratory Data Analysis, Box Plots, Statistics, Statistical Hypothesis Testing, Histogram, Probability & Statistics, Statistical Analysis, Statistical Programming, Statistical Machine Learning, Scikit Learn (Machine Learning Library), Python Programming
4.6
Rating, 4.6 out of 5 stars
3.3K reviews
Beginner · Specialization · 1 - 3 Months

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Statistics For Data Science
Skills you'll gain: Correlation Analysis, Probability & Statistics, Statistics, Statistical Analysis, Data Analysis, Data Science, Probability Distribution, Descriptive Statistics, Statistical Inference
4
Rating, 4 out of 5 stars
34 reviews
Beginner · Guided Project · Less Than 2 Hours
Status: Preview
Duke University
Data Science Math Skills
Skills you'll gain: Probability, General Mathematics, Bayesian Statistics, Calculus, Graphing, Descriptive Statistics, Algebra, Derivatives
4.5
Rating, 4.5 out of 5 stars
13K reviews
Beginner · Course · 1 - 3 Months
Status: Free Trial
DeepLearning.AI
Mathematics for Machine Learning and Data Science
Skills you'll gain: Linear Algebra, Descriptive Statistics, Statistical Hypothesis Testing, Bayesian Statistics, Probability Distribution, Probability & Statistics, Sampling (Statistics), Calculus, Applied Mathematics, Advanced Mathematics, A/B Testing, Statistics, Probability, Numerical Analysis, Mathematical Modeling, Statistical Analysis, Data Science, Machine Learning Algorithms, Dimensionality Reduction, Machine Learning
4.6
Rating, 4.6 out of 5 stars
2.8K reviews
Intermediate · Specialization · 1 - 3 Months
Status: Free Trial
Status: AI skills
IBM
IBM Data Science
Skills you'll gain: SQL, Unsupervised Learning, Data Wrangling, Matplotlib, Supervised Learning, Data Literacy, Relational Databases, Applied Machine Learning, Data Visualization Software, Professional Networking, Predictive Modeling, Plotly, Dashboard, Exploratory Data Analysis, Generative AI, Seaborn, Data Visualization, Data Mining, Jupyter, Data Science
Build toward a degree
4.6
Rating, 4.6 out of 5 stars
146K reviews
Beginner · Professional Certificate · 3 - 6 Months
Status: Free Trial
Johns Hopkins University
Data Science: Statistics and Machine Learning
Skills you'll gain: Rmarkdown, Shiny (R Package), Statistical Inference, Statistical Hypothesis Testing, Predictive Modeling, Regression Analysis, Exploratory Data Analysis, Statistical Analysis, Machine Learning Algorithms, Statistical Methods, Plotly, Statistics, Classification And Regression Tree (CART), R Programming, Data Visualization, Data Science, Statistical Modeling, Data Presentation, Machine Learning, GitHub
4.4
Rating, 4.4 out of 5 stars
7.2K reviews
Intermediate · Specialization · 3 - 6 Months
Status: Free Trial
IBM
Python for Data Science, AI & Development
Skills you'll gain: Jupyter, Web Scraping, Python Programming, Data Collection, Object Oriented Programming (OOP), Pandas (Python Package), Programming Principles, Data Structures, NumPy, Data Processing, Data Manipulation, Application Programming Interface (API), Data Import/Export, Computer Programming, Data Analysis
4.6
Rating, 4.6 out of 5 stars
42K reviews
Beginner · Course · 1 - 3 Months