collageFor aspiring professional statisticians, some schools offer online statistics degree programs. These are usually master’s degree programs that give advanced statistical theory and data analysis instruction and knowledge. Continue reading to learn more about online course delivery, common classes, and post-degree employment options.
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Online Statistics Courses for Credit
Free online courses in statistics are available for those seeking help in the subject without worrying about tuition or registration. However, if you’re looking for classes that can help you attain credit for school, these courses are a limited resource. Study.com can serve as a relatively low-cost option for those in need of credit. with online classes taught by professional instructors. These engaging courses contain both videos and transcripts of the lesson material, with practice quizzes to help you test yourself along the way.
Students can try out Statistics 101: Principles of Statistics, which covers content such as visual displays of data, matters of probability, and testing a hypothesis. Other topics discussed include:
- Sampling – Learn about random sampling, the law of large numbers, sampling distribution, and more.
- Regression & Correlation – Flesh out scatterplots, simple linear regression, residuals, and related statistical concepts.
- Summarizing Data – Delve into data set spreads, finding percentiles, calculating standard deviations, and related operations.
- Statistical Estimation – Some of the topics dealt with in this chapter include biased and unbiased estimators, using the t distribution, determining sample size, and calculating confidence intervals.
Free statistics courses are offered online for free at universities like the Massachusetts Institute of Technology and Carnegie Mellon University. Students can access course materials from each school’s website, though you won’t receive grades or college credit.
Where Can I Find Free Statistics Courses Online?
The following universities offer college-level statistics courses online. Although students cannot use their time online to earn college credit towards a degree or certificate program, much of the content of these courses is available to self-learners for free and without the need for registration or enrollment.
Massachusetts Institute of Technology
The Massachusetts Institute of Technology (MIT) first launched its OpenCourseWare site in 2000. Today, the school publishes almost its entire undergraduate and graduate course content online for free. Many undergraduate and graduate-level statistics courses are available through MIT’s mathematics OCW program, including:
- Introduction to Probability and Statistics goes over topics such as basic combinations, random variables, probability distributions, and more.
- Statistics for Applications looks at subjects like confidence intervals, hypothesis testing, chi-square tests, and related statistical uses.
- Statistical Learning Theory and Applications focuses on several core aspects of computational neuroscience while looking at concepts related to boosting and feature selection.
- Mathematical Statistics centers around decision theory and estimation while also examining topics like asymptotic efficiency of estimates.
MIT provides interested students with the chance to learn about statistics online for free. These courses cover areas of study like statistics for applications and nonparametrics and robustness.
- Topics in Statistics: Statistical Learning Theory
- Mathematical Statistics
- Statistics for Applications
- Topics in Statistics: Nonparametrics and Robustness
Carnegie Mellon University
Carnegie Mellon University (CMU) is a participant in the Open Learning Initiative, a sister project to OpenCourseWare. The OLI gathers data on student learning in order to provide feedback to instructors and course designers with the goal of creating useful, scientifically-based online courses that are available for free to all. OLI statistics courses offered through CMU include:
- Probability and Statistics examines fundamental concepts of statistical reasoning while breaking down various statistical applications and concepts of probability.
- Causal and Statistical Reasoning takes an in-depth look at the validity of statistical claims and presents methods of determining the value of such claims.
- Empirical Research Methods looks at topics such as random variables, data samples, interpreting graphs, and more.
Carnegie Mellon University offers courses in statistics online for free. Topics include logics and proofs, as well as causal and statistical reasoning. Students typically need specific software in order to fully engage with the provided course materials, including Flash, Java, Minitab or Statcrunch, depending on the course.
- Probability & Statistics
- Causal & Statistical Reasoning
- Logics and Proofs
Open University
The Open University, based in the United Kingdom, was founded with the mission of providing quality online learning. It has an open admissions policy, and enrolled students can earn a degree or certificate online. However, the school also offers many courses for free via an OpenLearn website, The Learning Space. Students can check out the following when searching for statistics courses:
- Finding Information in Mathematics and Statistics aims to help students identify and employ statistical information for a wide variety of purposes.
This course from Open University teaches students to work with data in boxplots and tabular form. Students can access multiple optional activities with solutions provided.
- Interpreting Data: Boxplots and Tables
Johns Hopkins University
The Bloomberg School of Public Health at Johns Hopkins University (JHSPH) offers its most popular courses online via OpenCourseWare. The school’s mission is to provide equal and open access to information about public health challenges and their solutions. The courses are, therefore, all related in some fashion to issues in world health. Statistics-related OpenCourseWare courses at JHSPH include:
- Introduction to Biostatistics goes over several matters of data and data types while serving as an introduction to biostatistical concepts and reasoning.
- Biostatistics for Medical Product Regulation fleshes out topics like basic study design, target population, comparison groups, and endpoints.
- Methods in Biostatistics I and II introduces concepts of applied probability, exploratory data analysis, and statistical interference while expanding on topics of probability models, variance, central limit theorem, and more.
- Statistics for Laboratory Scientists I and II looks at the basic applications of statistics within experimental biological sciences while demonstrating methods of exploring, organizing, and presenting data.
- Statistics for Psychosocial Research: Structural Models centers on quantitative approaches to constructing theory based on response variables while exploring topics like the statistical basis for causal inference; principles of path analysis; linear structural equation analysis, and related concepts.
- Statistics in Psychosocial Research: Measurement offers quantitative methods of measurement in psychological fields of study while delving into the principles of psychometrics, the statistical basis for latent variable analysis, and more.
The Bloomberg School of Public Health at Johns Hopkins University (JHSPH) offers its most popular courses online via OpenCourseWare. The school’s mission is to provide equal and open access to information about public health challenges and their solutions. The courses are, therefore, all related in some fashion to issues in world health. Statistics-related OpenCourseWare courses at JHSPH include:
- Introduction to Biostatistics goes over several matters of data and data types while serving as an introduction to biostatistical concepts and reasoning.
- Biostatistics for Medical Product Regulation fleshes out topics like basic study design, target population, comparison groups, and endpoints.
- Methods in Biostatistics I and II introduces concepts of applied probability, exploratory data analysis, and statistical interference while expanding on topics of probability models, variance, central limit theorem, and more.
- Statistics for Laboratory Scientists I and II looks at the basic applications of statistics within experimental biological sciences while demonstrating methods of exploring, organizing, and presenting data.
- Statistics for Psychosocial Research: Structural Models centers on quantitative approaches to constructing theory based on response variables while exploring topics like the statistical basis for causal inference; principles of path analysis; linear structural equation analysis, and related concepts.
- Statistics in Psychosocial Research: Measurement offers quantitative methods of measurement in psychological fields of study while delving into the principles of psychometrics, the statistical basis for latent variable analysis, and more.
Johns Hopkins University offers statistics courses online for free. Course topics include statistics for psychosocial research and statistics for laboratory scientists.
- Statistical Reasoning I
- Statistical Reasoning II
- Statistics for Laboratory Scientists I
- Statistics for Laboratory Scientists II
- Statistics for Psychosocial Research: Structural Models
- Statistics in Psychosocial Research: Measurement
University of California at Berkeley
The statistics course at UC Berkeley is designed for social and life scientists. Course emphasis is on statistical inferences. The Stat 2 course is available on iTunes as a set of audio podcast lectures.
- Statistics 131A
- Statistics 2
Free Online Statistics Courses At a Glance
| Course & School | Program Level | Format | Assignments | Quizzes & Exams | Downloadable |
|---|---|---|---|---|---|
| Topics in Statistics: Statistical Learning Theory course from MIT | Graduate | Text/lecture notes | Yes | No | Yes |
| Mathematical Statistics course from MIT | Graduate | Text/lecture notes/projects | Yes | Yes | Yes |
| Statistics for Applications course from MIT | Undergraduate | Text/lecture notes | Yes | Yes | Yes |
| Topics in Statistics: Nonparametrics and Robustness course from MIT | Graduate | Text/lecture notes | Yes | No | Yes |
| Probability & Statistics course from Carnegie Mellon University | Undergraduate | Text | Yes | Yes | No |
| Causal & Statistical Reasoning course from Carnegie Mellon University | Undergraduate | Text | Yes | Yes | No |
| Logics and Proofs course from Carnegie Mellon University | Undergraduate | Text | Yes | Yes | No |
| Interpreting Data: Boxplots and Tables course from Open University | Intermediate | Text | Yes | No | Yes |
| Statistical Reasoning I course from Johns Hopkins University | Unspecified | Text/audio | Yes | No | Yes |
| Statistical Reasoning II course from Johns Hopkins University | Unspecified | Text/audio | Yes | No | Yes |
| Statistics for Laboratory Scientists I course from Johns Hopkins University | Unspecified | Text | Yes | No | Yes |
| Statistics for Laboratory Scientists II course from Johns Hopkins University | Unspecified | Text | Yes | No | Yes |
| Statistics for Psychosocial Research: Structural Models course from Johns Hopkins University | Unspecified | Text | Yes | No | Yes |
| Statistics in Psychosocial Research: Measurement course from Johns Hopkins University | Unspecified | Text | Yes | No | Yes |
| Statistics 131A course from UC Berkeley | Undergraduate | Video lectures | No | No | Yes |
| Statistics 2 course from UC Berkeley | Undergraduate | Audio podcast | No | No | Yes |
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