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As a complete beginner, what is the best place to learn stats and math for data science online?
Hello! Thanks for your question about what is the best place for complete beginners to learn stats and math for data science online. The short version is that the top 5 rated online courses that help adults develop the math and statistics foundations to study data science are Foundations of Data Analysis (University of Texas at Austin), Statistics with R Specialization (Duke University), Introduction to Probability -The Science of Uncertainty (Massachusetts Institute of Technology), MedStats: Statistics in Medicine (Stanford University), and I “Heart” Stats: Learning to Love Statistics (University of Notre Dame). Below you will find a deep dive of my findings.
METHODOLOGY
I have scoured the Internet for articles related to this subject. I discovered an article on Free Code Camp where the author has identified every online introduction to statistics and probability course offered as of November 2016, extracting key bits of information from their syllabi and reviews. He then evaluated the courses by compiling average rating and number of reviews from Class Central and other review sites and calculated a weighted average rating for each course.
Each course fits four criteria:
1. It must be an introductory course with little to no statistics or probability experience required.
2. It must be on-demand or offered every few months.
3. It must be at least ten hours in total for estimated completion.
4. It must be an interactive online course, so no books or read-only tutorials.
1. FOUNDATIONS OF DATA ANALYSIS BY UNIVERSITY OF TEXAS AT AUSTIN (EDX)
“Foundations of Data Analysis” includes two of the top reviewed statistics courses available with a weighted average rating of 4.48 out of 5 stars over 20 reviews. The series is one of the only courses in the upper echelon of ratings to teach statistics with a focus on coding up examples. These courses together have a great mix of fundamentals coverage and scope for the beginner data scientist. Part 1 of the course will walk through the basics of statistical thinking. In the second part of a two-part statistics course, students will learn how to take data and use it to make reasonable and useful conclusions.
- Price: Free
- Timeline: 6 weeks at 3–6 hours per week for each course
- Benefits: Learners will leave the course with the ability to use basic statistical techniques to answer their questions about their data, using a widely available statistical software package (R).
2. STATISTICS WITH R SPECIALIZATION BY DUKE UNIVERSITY (COURSERA)
This five-course specialization is based on Duke’s Data Analysis and Statistical Inference course, which had a 4.82-star weighted average rating over 55 reviews. The syllabi are comprehensive and have full sections dedicated to probability. In this Specialization, students will learn to analyze and visualize data in R and created reproducible data analysis reports, demonstrate a conceptual understanding of the unified nature of statistical inference, perform frequentist and Bayesian statistical inference and modeling to understand natural phenomena and make data-based decisions, communicate statistical results correctly, effectively, and in context without relying on statistical jargon, critique data-based claims and evaluated data-based decisions, and wrangle and visualize data with R packages for data analysis.
- Price: Free
- Timeline: 4–5 weeks at 5–7 hours per week for each course
- Benefits: Students will produce a portfolio of data analysis projects from the Specialization that demonstrates mastery of statistical data analysis from exploratory analysis to inference to modeling. These skills are suitable for applying for statistical analysis or data scientist positions.
3. INTRODUCTION TO PROBABILITY - THE SCIENCE OF UNCERTAINTY BY THE MASSACHUSETTS INSTITUTE OF TECHNOLOGY (MIT)
The above course provides a deep dive into the world of probability. It has a weighted average rating of 4.91 out of 5 stars over 34 reviews. However, it is challenging and much longer than most MOOCs. The level of which the course covers probability is also not necessary for the data science beginner. Instead of relying on the traditional "theorem - proof" format, the trainers develop the material in an intuitive but still rigorous and mathematically precise manner. Furthermore, while the applications are multiple and evident, the course emphasizes the basic concepts and methodologies that are universally applicable.
- Price: Free
- Timeline: 16 weeks at 12 hours per week
- Benefits: Enable students to apply the tools of probability theory to real-world applications or their research.
4. MEDSTATS: STATISTICS IN MEDICINE BY STANFORD UNIVERSITY (STANFORD OPENEDX)
Great syllabus where the examples have medical a focus. A worthy option for anyone, even those not targeting medicine. It has a 4.58-star weighted average rating over 32 reviews. The course focuses on real examples from the medical literature and popular press. Each week starts with "teasers," such as should I be worried about lead in lipstick? The trainers will work their way back from the news coverage to the original study and then to the underlying data. In the process, participants will learn how to read, interpret, and critically evaluate the statistics in medical studies.
- Price: Free
- Timeline: 10 weeks, Self-paced
- Benefits: Participants will learn how to read, interpret, and critically evaluate the statistics in medical studies. The course also prepares participants to be able to analyze their data, guiding them on how to choose the correct statistical test and how to avoid common statistical pitfalls.
5. I “HEART” STATS: LEARNING TO LOVE STATISTICS BY UNIVERSITY OF NOTRE DAME (EDX)
This course targets a non-technical audience. No coding is involved, has good production value, and course and instructors look fun. It has a 4.54-star weighted average rating over 12 reviews. The purpose of this course is to help learners develop a functional, satisfying, and useful life-long relationship with statistics. To achieve that goal, the trainers will take a non-technical approach where students will learn how statistics work and why they are so helpful in evaluating the world of information that is around us. They will learn about the logic of statistical thinking and the concepts (rather than the mathematical details and probability theory) that guide statistical inferences and conclusions.
- Price: Free
- Timeline: 9 weeks at 4-6 hours per week
- Benefits: Students would be able to identify the most important features of a data set, select a statistical test based on the features of the data, think like a statistical detective, understand the relationship between two different characteristics or variables, perform some simple statistical calculations and draw some conclusions from real data, and “love” statistics.
CONCLUSION
To wrap it up, the top 5 rated online courses that help adults develop the math and statistics foundations to study data science are Foundations of Data Analysis, Statistics with R Specialization, Introduction to Probability -The Science of Uncertainty, MedStats: Statistics in Medicine, and I “Heart” Stats: Learning to Love Statistics. The weighted average ratings of these courses range from 4.48 to 4.91 out of 5 stars. These courses are available for free online, and it takes at least ten hours in total to complete the full course. Besides preparing students for a career in data science, the benefits of taking these courses include developing the ability to use available statistical software package (R) to answer their own questions about their own data, learning skills suitable for applying for statistical analysis positions, learning how to apply the tools of probability theory to real-world applications, critically evaluate the statistics in medical studies, and learning how to “love” statistics. Thanks for using Wonder! Please let us know if we can help with anything else!