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Applied Statistics Courses Online

Understand applied statistics for data analysis and interpretation. Learn statistical methods and tools for various industries.

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Explore the Applied Statistics Course Catalog

  • Status: New
    New
    Status: Free Trial
    Free Trial
    U

    University of Colorado Boulder

    Foundations of Probability and Statistics

    Skills you'll gain: Probability, Markov Model, Estimation, Probability & Statistics, Probability Distribution, Statistical Methods, Statistical Inference, Bayesian Statistics, Sampling (Statistics), Statistical Analysis, Mathematical Modeling, Statistics, Statistical Modeling, Data Analysis, Data Science, Descriptive Statistics, Machine Learning Algorithms, Artificial Intelligence, Generative AI

    Build toward a degree

    4.4
    Rating, 4.4 out of 5 stars
    ·
    311 reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: Preview
    Preview
    S

    Stanford University

    Introduction to Statistics

    Skills you'll gain: Descriptive Statistics, Statistics, Statistical Methods, Sampling (Statistics), Statistical Analysis, Data Analysis, Statistical Modeling, Statistical Hypothesis Testing, Regression Analysis, Statistical Inference, Probability, Exploratory Data Analysis, Quantitative Research, Probability Distribution

    4.6
    Rating, 4.6 out of 5 stars
    ·
    4.2K reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    D

    DeepLearning.AI

    Applied Statistics for Data Analytics

    Skills you'll gain: Probability & Statistics, Statistical Analysis, Statistics, Data Visualization, Statistical Hypothesis Testing, Descriptive Statistics, Data Analysis, Statistical Methods, Probability Distribution, Correlation Analysis, Statistical Inference, Sampling (Statistics), Large Language Modeling, LLM Application

    4.9
    Rating, 4.9 out of 5 stars
    ·
    40 reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    M

    Meta

    Statistics Foundations

    Skills you'll gain: Bayesian Statistics, Descriptive Statistics, Statistical Hypothesis Testing, Statistical Inference, Sampling (Statistics), Data Modeling, Statistics, Probability & Statistics, Statistical Analysis, Statistical Methods, Statistical Modeling, Marketing Analytics, Tableau Software, Data Analysis, Spreadsheet Software, Analytics, Time Series Analysis and Forecasting, Regression Analysis

    4.7
    Rating, 4.7 out of 5 stars
    ·
    362 reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of Michigan

    Statistics with Python

    Skills you'll gain: Sampling (Statistics), Statistical Hypothesis Testing, Statistical Modeling, Statistical Methods, Statistical Inference, Data Visualization, Descriptive Statistics, Bayesian Statistics, Data Visualization Software, Jupyter, Histogram, Statistical Software, Probability & Statistics, Matplotlib, Statistical Analysis, Statistics, Data Analysis, Box Plots, Statistical Programming, Python Programming

    4.6
    Rating, 4.6 out of 5 stars
    ·
    3.3K reviews

    Beginner · Specialization · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Advanced Statistics for Data Science

    Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Regression Analysis, Bayesian Statistics, Statistical Analysis, Probability & Statistics, Statistical Inference, Statistical Methods, Statistical Modeling, Linear Algebra, Probability, R Programming, Biostatistics, Data Science, Statistics, Probability Distribution, Mathematical Modeling, Data Analysis, Applied Mathematics, Predictive Modeling

    4.4
    Rating, 4.4 out of 5 stars
    ·
    777 reviews

    Advanced · Specialization · 3 - 6 Months

What brings you to Coursera today?

  • Status: Free Trial
    Free Trial
    G

    Google

    The Power of Statistics

    Skills you'll gain: Sampling (Statistics), Descriptive Statistics, Statistical Hypothesis Testing, Data Analysis, Probability Distribution, Statistics, Data Science, Statistical Analysis, A/B Testing, Statistical Methods, Probability, Statistical Inference, Statistical Programming, Python Programming, Technical Communication

    4.8
    Rating, 4.8 out of 5 stars
    ·
    843 reviews

    Advanced · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of Amsterdam

    Methods and Statistics in Social Sciences

    Skills you'll gain: Qualitative Research, Scientific Methods, Statistical Analysis, Statistical Hypothesis Testing, Research, Research Design, Sampling (Statistics), Research Reports, Science and Research, Interviewing Skills, Data Analysis, Data Collection, Research Methodologies, Social Sciences, Surveys, Quantitative Research, Statistics, Regression Analysis, Statistical Inference, R Programming

    4.6
    Rating, 4.6 out of 5 stars
    ·
    7.8K reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    U

    University of Maryland, College Park

    Survey Data Collection and Analytics

    Skills you'll gain: Sampling (Statistics), Sample Size Determination, Surveys, Survey Creation, Data Collection, Statistical Analysis, Interviewing Skills, Research Design, STATA (Software), R (Software), Data Integration, Data Ethics, Stata, Data Quality, Statistical Modeling, Qualitative Research, Descriptive Statistics, Data Cleansing, Statistical Software, R Programming

    4.4
    Rating, 4.4 out of 5 stars
    ·
    1.4K reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    U

    University of Amsterdam

    Basic Statistics

    Skills you'll gain: Statistical Hypothesis Testing, Statistics, Scientific Methods, Quantitative Research, Data Analysis Software

    4.6
    Rating, 4.6 out of 5 stars
    ·
    4.6K reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of California, Santa Cruz

    Bayesian Statistics

    Skills you'll gain: Time Series Analysis and Forecasting, Bayesian Statistics, R Programming, Forecasting, Statistical Inference, Statistical Modeling, Technical Communication, Data Presentation, Statistics, Probability, Statistical Analysis, Statistical Software, Advanced Analytics, R (Software), Data Analysis, Mathematical Modeling, Microsoft Excel, Markov Model, Statistical Methods, Data Science

    4.6
    Rating, 4.6 out of 5 stars
    ·
    3.5K reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    U

    University of Michigan

    Applied Machine Learning in Python

    Skills you'll gain: Feature Engineering, Applied Machine Learning, Supervised Learning, Scikit Learn (Machine Learning Library), Predictive Modeling, Machine Learning, Decision Tree Learning, Unsupervised Learning, Python Programming, Dimensionality Reduction, Random Forest Algorithm, Regression Analysis

    4.6
    Rating, 4.6 out of 5 stars
    ·
    8.6K reviews

    Intermediate · Course · 1 - 4 Weeks

Applied Statistics learners also search

R Statistics
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Advanced Statistics
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1234…223

In summary, here are 10 of our most popular applied statistics courses

  • Foundations of Probability and Statistics: University of Colorado Boulder
  • Introduction to Statistics: Stanford University
  • Applied Statistics for Data Analytics: DeepLearning.AI
  • Statistics Foundations: Meta
  • Statistics with Python: University of Michigan
  • Advanced Statistics for Data Science: Johns Hopkins University
  • The Power of Statistics: Google
  • Methods and Statistics in Social Sciences: University of Amsterdam
  • Survey Data Collection and Analytics: University of Maryland, College Park
  • Basic Statistics: University of Amsterdam

Frequently Asked Questions about Applied Statistics

Applied statistics is the use of statistical techniques to solve real-world data analysis problems. In contrast to the pure study of mathematical statistics, applied statistics is typically used by and for non-mathematicians in fields ranging from social science to business. Indeed, in the big data era, applied statistics has become important for deriving insights and guiding decision-making in virtually every industry.

The increased reliance on data and statistics to help understand our world has made the careful application of these techniques even more essential; too often, statistics can be used erroneously or even misleadingly when methods of analysis are not properly connected to research questions. Thus, a major aspect of applied statistics is the accurate communication of findings for a non-technical audience, including specifics about data sources, relevance to the problem at hand, and degrees of uncertainty.

That said, the statistical approaches used in this field are the same as in the study of mathematical statistics. Rigorous use of statistical hypothesis testing, statistical inference, linear regression techniques, and analysis of variance (ANOVA) are core to the work of applied statistics. And, as in other areas of data science, Python programming and R programming are often used to analyze large datasets when Microsoft Excel is not sufficiently powerful.‎

Demand for data-driven insights is growing fast across all fields, making a background in applied statistics the gateway to a wide variety of careers. Financial institutions and companies of all kinds rely on business analytics to guide investments and operations; political candidates and advocacy groups need to conduct surveys and understand public polling data to understand popular opinion on today’s issues; and even sports teams are increasingly hiring experts in applied statistics to make decisions regarding personnel as well as in-game strategy.

While many jobs in applied statistics may require only a bachelor’s degree in fields such as mathematics or computer science, high-level roles often expect a master’s degree in statistics. According to the Bureau of Labor Statistics, professional statisticians earn a median annual salary of $91,160 as of May 2019, and these jobs are expected to grow much faster than average due to the need to analyze fast-growing volumes of electronic data.‎

Yes, with absolute certainty. Coursera offers courses and Specializations in applied statistics for business, social science, and other areas, as well as related topics such as data science and Python programming. These courses are offered by top-ranked universities and leading companies from around the world, including the University of Michigan, the University of Amsterdam, and the University of Virginia, and IBM. Regardless of whether you’re a student looking to learn more about this exciting field or a mid-career professional upgrading their skill set, the combination of a high-quality education and the flexibility of learning online makes Coursera a great choice.‎

It's very helpful to have strong math skills, analytical skills, and experience solving problems before starting to learn applied statistics. It's also good to have experience and a good comfort level with technology and computers. Previous experience in statistics is also helpful, although not required. You may also benefit from having prior experience using Excel spreadsheets as you begin to learn applied statistics.‎

People best suited for roles in applied statistics are analytical thinkers. They enjoy problem-solving by taking available data and analyzing it to arrive at solutions. They also have effective communication skills so that information can flow clearly to all stakeholders within an organization. Organization and multitasking come easily to people best suited for roles in applied statistics because these individuals need to deal with large amounts of information and manage their time and resources efficiently. People well suited for these roles also pay close attention to detail to make sure the outcomes they're tasked with delivering meet or exceed expectations.‎

While the use of applied statistics can be found in almost every industry, learning applied statistics may be especially interesting to you if you're seeking a career in the insurance, web analytics, or energy sectors. These are some of the top industries that currently utilize applied statistics. However, a person in any position in which data is gathered and analyzed to create solutions, innovations, or improvements would benefit from learning applied statistics, from coaches and hospital administrators to bloggers, data scientists, and bankers. If you would like to know how to ensure you're collecting the right data, how to analyze data correctly, and how to effectively report your findings so they can be applied in real-world situations, learning applied statistics may be right for you.‎

Online Applied Statistics courses offer a convenient and flexible way to enhance your existing knowledge or learn new Applied Statistics skills. With a wide range of Applied Statistics classes, you can conveniently learn at your own pace to advance your Applied Statistics career skills.‎

When looking to enhance your workforce's skills in Applied Statistics, 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.‎

This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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