Open Online Courses in Statistics

What is Statistics?

Statistics is an academic discipline concerned with the collection, graphic representation, and analysis of data taken from specific population surveys. College statistics programs often focus on three subsections of statistical study: applied, theoretical, and mathematical statistics. Applied statistics courses consolidate the study of descriptive and inferential statistics, which uses results from probability studies to explain clear numeric correlations in data as well as the more random results. On-campus and online statistics courses that discuss theoretical statistics use logic and probability theory to explain why data sets yield certain results while mathematical statistics are concerned with fundamentally altering experiment designs to create different probability data.

What Can Online Courses in Statistics Actually Teach Me?

If you plan on enrolling in an online statistics course, you should know that there are no accrediting agencies for statistics courses or programs around the country. The American Statistical Association (AMSTAT) does offer voluntary accreditation to tenured statistics professors with an advanced statistics degree and over 5 years of teaching experience, but there are no ubiquitous accreditation criteria for online courses in statistics. Any online statistics class can teach you about probability theory, confounding factors, and numeric correlations, but the key aspect of this field is experimentation and sample survey design. Online courses simply cannot fulfill this portion of your statistics education since it is up to you to go out, design experiments, and use analytical thinking to explain results from any particular data set.

Online courses in statistics are useful tools for learning about probability theory, experiment design, inferential statistics, and data mining. During these courses, you will ask yourself questions such as:

  • Which experiment factors have direct numeric correlations with one another?
  • Which factors in the sample survey are confounding and fail to fully explain seemingly random experimental results?
  • Did I choose a diverse set of people for my statistical sample?
  • Does my data corroborate my hypothesis?
  • How would changing fundamental aspects of my statistical survey alter the results?

Since there are no criteria for university or online-based statistics courses, you will have to rely upon your own independent research and discretion when selecting a relevant, informative course. Before enrolling, you should research the prestige of the school, the positions its graduates hold in the job market, as well as whether your professor has a PhD in statistics. Accredited postsecondary schools only hire faculty with doctorates in their field, so any college that falls short of that hiring criteria probably lacks an informative, current statistics curriculum. Largely populated universities often have online portals dedicated to student course reviews. You should heed the insight of students whom took your desired courses in the past when deciding if they fit your academic needs.

Free Online Courses in Statistics From Around the Web

We have compiled relevant open courseware in statistics and organized it in the directory below. Open courseware is simply a collection of online tests, video lectures, and related course materials from mostly prestigious universities from around the world. While these materials are non-restrictive and free to access, you will have to learn independently since you cannot interact with the professor of the course. However, these courses can be excellent resources if you are considering an on-campus or online statistics degree and want to gauge your interest in the subject matter and ability to meet classroom work requirements.

Subjects

Statistics (4)

Introduction to Applied StatisticsUMass Boston

Open Courseware

Probability, Mathematics, Logic
Taught by: Professor Eugene Gallagher, Ph.D.

Course Description:

Through use of the materials in this online course, you can learn how to use statistics to model practical problems in science and engineering. To get the most out of this course, you will need MATLAB, a statistics software package for performing scientific research, as much of the course focuses on MATLAB data analysis. The materials for this course were originally offered as a graduate course in the summer of 2011, so having a background in an engineering or science field is required to get the most out of the materials.

Introduction to Statistics and Data AnalysisUniversity of Michigan

Open Courseware

Data Analysis, Mathematics, Probability
Taught by: Brenda Gunderson

Course Description:

If you are looking for further information on statistical methods, such as frequency distributions, basic probability, and regression, this online course is a good place to start. Created for undergraduate students for a course offered in the winter of 2013, this course only requires a means of reading Microsoft Word or PDF documents to access the course materials. Not limited to lecture notes, this course also provides workbook activities for students who want to practice their statistical skills.

Statistical ReasoningCarnegie Mellon University

Open Courseware

Probability, Mathematics, Logic

Course Description:

These materials from an undergraduate online course are offered by the Open Learning Intiative at Carnegie Mellon University, and will teach you about basic logic for statistical reasoning. This course will also teach you how to apply statistics to real world situations and other fields of study, and assumes no prior knowledge about statistics. You will need statistical analysis software like Microsoft Excel or StatCrunch, as well as Flash and Java, to complete the exercises offered by the course.

Patients and Populations: Medical Decision-MakingUniversity of Michigan

Open Courseware

Healthcare, Biostatistics, Population Science
Taught by: Rajesh Mangrulkar, Stephen Gruber

Course Description:

This online course focuses on the medical practitioner’s responsibility to make sound decisions related to patient care based on genetics, epidemiology, information gathering and health assessment. Through this course, you will develop an in-depth understanding of fundamental concepts in biostatistics and research and design in order to effectively and systematically apply probabilistic reasoning to diagnostic issues that arise in clinical situations. Originally published as open courseware in 2012, this course is intended for first-year medical students with backgrounds in health and medicine.