Foundations of Data Analysis - Part 1: Statistics Using R

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Foundations of Data Analysis - Part 1: Statistics Using R

Course Details

Cost

FREE

Upcoming Schedule

  • On demand

Course Provider

edX online courses
Harvard University, the Massachusetts Institute of Technology, and the University of California, Berkeley, are just some of the schools that you have at your fingertips with edX. Through massive open online courses (MOOCs) from the world's best universities, you can develop your knowledge in literature, math, history, food and nutrition, and more. These online classes are taught by highly-regarded experts in the field. If you take a class on computer science through Harvard, you may be tau...
Harvard University, the Massachusetts Institute of Technology, and the University of California, Berkeley, are just some of the schools that you have at your fingertips with edX. Through massive open online courses (MOOCs) from the world's best universities, you can develop your knowledge in literature, math, history, food and nutrition, and more. These online classes are taught by highly-regarded experts in the field. If you take a class on computer science through Harvard, you may be taught by David J. Malan, a senior lecturer on computer science at Harvard University for the School of Engineering and Applied Sciences. But there's not just one professor - you have access to the entire teaching staff, allowing you to receive feedback on assignments straight from the experts. Pursue a Verified Certificate to document your achievements and use your coursework for job and school applications, promotions, and more. EdX also works with top universities to conduct research, allowing them to learn more about learning. Using their findings, edX is able to provide students with the best and most effective courses, constantly enhancing the student experience.

Provider Subject Specialization
Sciences & Technology
Business & Management
22696 reviews

Course Description

In this first part of a two part course, we’ll walk through the basics of statistical thinking – starting with an interesting question. Then, we’ll learn the correct statistical tool to help answer our question of interest – using R and hands-on Labs. Finally, we’ll learn how to interpret our findings and develop a meaningful conclusion.

This course will consist of:

  • Instructional videos for statistical concepts broken down into manageable topics
  • Guided questions to help your understanding of the topic
  • Weekly tutorial videos for using R Scaffolded learning with Pre-Labs (using R), followed by Labs where we will answer specific questions using real-world datasets
  • Weekly wrap-up questions challenging both topic and application knowledge

We will cover basic Descriptive Statistics – learning about visualizing and summarizing data, followed by a “Modeling” investigation where we’ll learn about linear, exponential, and l...

In this first part of a two part course, we’ll walk through the basics of statistical thinking – starting with an interesting question. Then, we’ll learn the correct statistical tool to help answer our question of interest – using R and hands-on Labs. Finally, we’ll learn how to interpret our findings and develop a meaningful conclusion.

This course will consist of:

  • Instructional videos for statistical concepts broken down into manageable topics
  • Guided questions to help your understanding of the topic
  • Weekly tutorial videos for using R Scaffolded learning with Pre-Labs (using R), followed by Labs where we will answer specific questions using real-world datasets
  • Weekly wrap-up questions challenging both topic and application knowledge

We will cover basic Descriptive Statistics – learning about visualizing and summarizing data, followed by a “Modeling” investigation where we’ll learn about linear, exponential, and logistic functions. We will learn how to interpret and use those functions with basic Pre-Calculus. These two “units” will set the learner up nicely for the second part of the course: Inferential Statistics with a multiple regression cap.

Both parts of the course are intended to cover the same material as a typical introductory undergraduate statistics course, with an added twist of modeling. This course is also intentionally devised to be sequential, with each new piece building on the previous topics. Once completed, students should feel comfortable using basic statistical techniques to answer their own questions about their own data, using a widely available statistical software package (R).

With these new skills, learners will leave the course with the ability to use basic statistical techniques to answer their own questions about their own data, using a widely available statistical software package (R). Learners from all walks of life can use this course to better understand their data, to make valuable informed decisions.

Join us in learning how to look at the world around us. What are the questions? How can we answer them? And what do those answers tell us about the world we live in?

Reviews 9/10 stars
23 Reviews for Foundations of Data Analysis - Part 1: Statistics Using R

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Rankings are based on a provider's overall CourseTalk score, which takes into account both average rating and number of ratings. Stars round to the nearest half.

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J Kim profile image
J Kim profile image
10/10 starsCompleted
  • 2 reviews
  • 1 completed
2 months, 3 weeks ago
extremely satisfied. I tried many different R courses so far, and this was the best MOOC stat/R course I have ever had. very good course material and instruction video.
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Mike Taylor profile image
Mike Taylor profile image
8/10 starsCompleted
  • 6 reviews
  • 6 completed
5 months, 2 weeks ago
This was a well done course and I learned a lot - especially about R. For someone without some knowledge of statistics, it might prove very challenging. I am a math teacher and was largely able to skip of the math portion and concentrate on the analysis using R. They offered lots of supplemental reading for increasing an understanding of stats and did some basic explanation of the concepts but without understanding things like r-squared and exponential functions, SOME students might get frustrated. I'm generally a fan of the EdX setup and found they did a good job of providing the right amount of comprehension checks - in fact, sometimes this got a little repetitive and I just skipped some problems if I felt I already got the point and didn't want to do the calculations. Overall I would recommend this course if you are looking to learn more about R while reviewing your knowledge of basic statistics.
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Steve Lai profile image
Steve Lai profile image

Steve Lai

10/10 starsCompleted
1 year, 10 months ago
I completed this course under the Audit track, even though I didn't bother with a certificate. This is an excellent course. It teaches not only statistics in a clear, easily understood manner, but also cultivates in the student a structured and methodical way to tackle statistical research questions. The lecture videos and R tutorial videos are well presented and delivered. You can also download PDF transcripts of the R tutorials, which is handy for copying the commands into RStudio. I like especially the Pre-Lab and Lab exercises. R scripts are provided for the Pre-Labs, though you have to adapt these to do the Labs and later on the problem sets. The teaching staff have obviously put a lot of thought into designing the Pre-Labs and Lab exercises. Each one clearly states the primary research questions to be answered statistically. You are then guided to do initial exploration to understand the available data first, then reflect o... I completed this course under the Audit track, even though I didn't bother with a certificate. This is an excellent course. It teaches not only statistics in a clear, easily understood manner, but also cultivates in the student a structured and methodical way to tackle statistical research questions. The lecture videos and R tutorial videos are well presented and delivered. You can also download PDF transcripts of the R tutorials, which is handy for copying the commands into RStudio. I like especially the Pre-Lab and Lab exercises. R scripts are provided for the Pre-Labs, though you have to adapt these to do the Labs and later on the problem sets. The teaching staff have obviously put a lot of thought into designing the Pre-Labs and Lab exercises. Each one clearly states the primary research questions to be answered statistically. You are then guided to do initial exploration to understand the available data first, then reflect on why a particular test is the appropriate tool to be used. You are also taught how to break down the analysis into logical steps - subsetting the data, checking that the assumptions required by a test is met, getting a better feel of the data by visualisation etc. before actually carrying out the analysis in R and interpret the results. I like especially the way they made available (after the questions are completed) videos feedback on Pre-Lab questions, so you can learn why and where you made errors. A pity though that the same is not available for the Lab exercises and the problem sets. The Lab conclusions are canned paragraphs where you have to fill in the gaps. The course doesn't explicitly teach how to write reports, but you can learn from these canned paragraphs how to write succinct but comprehensive conclusions. The course reading materials seem to be extracts from some open source text. They complement the lecture videos well . The problem sets are good for testing comprehension, though I found that it is very easy to make careless mistakes and lose mark. I suppose it is a way for the course team to teach students to read the questions carefully. For example, it won't do to just copy the R output into the answer box when the question asked for an answer in percentage format, but without the percentage sign. Overall, I thoroughly enjoyed the course and glad that I invested the time in doing it. So much so that I went on and also completed the follow-up course, Foundations of Data Analysis - Part 2. I can highly recommend this course to anyone who wants to learn statistics, or R, or simply want clearer teaching if they struggle with other statistic course that they are doing.
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Michael Smith profile image
Michael Smith profile image

Michael Smith

10/10 starsCompleted
2 years, 3 months ago
This is the most useful stats course available on the internet because it teaches the content in R, and it guides the thinking of the student with critical comprehension questions throughout. You'll want to start asking your own research questions with your own data set as soon as you're done. (And I've taken part 2 as well, which I consider just as essential)
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Leandro Coelho profile image
Leandro Coelho profile image

Leandro Coelho

10/10 starsTaking Now
2 years, 4 months ago
I'll have to agree with most of the reviews here and say: this is the best MOOC course I've ever taken, the material is amazing and very practical, the professor is absolutely awesome and shows a very deep knowledge of the subject, by the end of the two parts of this course you'll have a strong foundation on statistics and a good grasp of R being able to apply what you learned in real life. I strongly recommend this course, and I also would like to thank Dr. Mahometa for his excellent work and dedication to this course.
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Guillermo Naranjo profile image
Guillermo Naranjo profile image

Guillermo Naranjo

10/10 starsCompleted
2 years, 4 months ago
I really enjoyed this course and will start the second part next. The content is very good organized, Mr Michael Mahometa does a great job explaining the concepts. The exercises and dataset are very interesting.
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Darren Rippy profile image
Darren Rippy profile image

Darren Rippy

10/10 starsCompleted
2 years, 5 months ago
This course is a solid introduction to thinking statistically about data. The focus is not on memorizing formulas, but rather on understanding the meaning behind certain statistics and proper methods to apply given the data. The readings, both mandatory and optional, were easy to understand, again with an emphasis to understanding the methods rather than mechanical calculations. Easy lesson progresses from an step-by-step R tutorial to a pre-lab, lab, and problem set, respectively. Each guides you to answering questions more independently using R to reason statistically about the data. This course really is a great introduction to statistical reasoning.
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Sumendar Karupakala profile image
Sumendar Karupakala profile image

Sumendar Karupakala

10/10 starsCompleted
2 years, 5 months ago
Most promising course for aspiring data analysts/data scientists, The whole arrangement of the content using step by step approach by providing topic wise reference documents was really astonishing.
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student profile image
student profile image

student

10/10 starsCompleted
3 years, 7 months ago
Basically an introductory course to statistics, good for people with no previous experience, but also for those willing to refresh some concepts. R is used as a tool,learning how to use it is not the focus of the course. Although it was useful as a good first contact with the program, because video tutorials are clear and straight to the point, and allow you to see what R can do. Material is very well organized, content is clear and focus on main ideas. Exercises help to understand key concepts. I totally recommend it, and also Part 2.
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John Rosenfelder profile image
John Rosenfelder profile image

John Rosenfelder

10/10 starsCompleted
3 years, 6 months ago
One of the best online classes I have ever taken, out of about 20. Excellent material, clearly presented and good level of challenge for an novice data analyst. Dr. Mahometa also has excellent office hours where he shares deeper explanations with the students. I strongly recommend him and this class!
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Fernando Pellegrini profile image
Fernando Pellegrini profile image

Fernando Pellegrini

9/10 starsCompleted
3 years, 7 months ago
Really really well organized course. It serves well as a introduction to basic satistic concepts and to R language. The staff was active and usually responded to all forum questions.
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student profile image
student profile image

student

10/10 starsCompleted
3 years, 9 months ago
very interesting! especially the integration with R coding! every week is introduced by a brief chapter ad a small lecture about the subject. the solutions for the exercises are always very well explained.
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V R profile image
V R profile image

V R

10/10 starsCompleted
3 years, 9 months ago
Excellent Course!! One of the best courses to get introduced to statistics with R. Both sets of videos - statistics and R - explain the concepts clearly. The assignments were not difficult though. Maybe having a few difficult assignments will improve the course.
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Jorge J profile image
Jorge J profile image

Jorge J

10/10 starsCompleted
3 years, 9 months ago
I enjoyed this course very much! All the examples are carefully built on previous ones and the R tutorials are clear and simple. Dr Mahometa and team have done an exceptional work with this course. The topics covered are: Introduction to Data, Univariate Descriptive Statistics, Bivariate Distributions (Numerical and Categorical Data), Linear Functions,and Exponential and Logistic Function Models. That's in 6 weeks with more or less 5 hours of work per week.
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Mavis He profile image
Mavis He profile image

Mavis He

10/10 starsCompleted
3 years, 9 months ago
The best course teaching R that I've found by now. The R programming course provided by JHU on Coursera is kind of too difficult for a beginner in R. But this course provided by UT is highly practical, easy and very funny to learn. The R tutorial is very helpful and we can have great chances to directly apply what we've learned from the video lectures to the Pre-lab, Lab and problem sets. I love UT-Austin!! Many thanks to all the great teachers from UT
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Student profile image
Student profile image

Student

10/10 starsCompleted
3 years, 9 months ago
Well structured, weekly live (and archived) office hours and excellent content. Topics are covered in short, but focused videos. Hands on homework include "check your understanding" quizs, and pre lab and lab assignments. Seperate weekly videos include using R and RStudio to complete projects. All data sets are furnished and are interesting examples of real world data. This course requires students' strong time commitment, but is worth it.
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student

10/10 starsCompleted
3 years, 9 months ago
The best introductory course for statistical use of R!!! The videos are very didactic and it teaches step by step each lesson, as well as the R language. The way the exercises and tests are proposed is very stimulating. I'm waiting for the next course!!!
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Student profile image

Student

8/10 starsTaking Now
3 years, 9 months ago
I am working as a Biochemist in a large R&D structure. I registered to learn how to use R and to refresh/learn basic statistics or at the leas when and why use which approach. So far this course has fully met my expectations, it is very well done, very interesting and tutorials are terrific. The reading part is also well done and contains numerous examples to train oneself. The Pre-Lab, Lab and Problem sets are also really good into evaluating how we perform. It's also possible to go a bit more into depth using optional readings. I'm glad I registered for the second course.
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student profile image

student

4/10 starsTaking Now
3 years, 9 months ago
Curso de estadística básica con algo de R muy introductorio. Si tienes carrera de ingeniería o ciencias no aprenderás nada nuevo. Interesante solo si no has visto R nunca pero lo que aprendes se hace mas rapido en excell o spss. Eso si, el profesor explica muy bien y los videos de R son claros. Los examenes, lab y problem sets, solo tienen un intento. Lo voy a terminar pero no hare la segunda parte. Por otr lado, Ya no dan honor code , lo que hace que EDx pierda gracia. En coursera al menos dan financial aid.
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AL QUE profile image
AL QUE profile image

AL QUE

10/10 starsTaking Now
3 years, 9 months ago
This is one of the best courses out there, definitely recommend to any one, really hard work has gone into this course in preparation.
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collins kipchumba profile image
collins kipchumba profile image

collins kipchumba

10/10 starsTaking Now
3 years, 10 months ago
To work in a highly result oriented organization, using my professional qualifications in line with the organization policy, procedures professional standards and statutory requirements
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Javier Garcia profile image
Javier Garcia profile image

Javier Garcia

10/10 starsCompleted
4 years, 1 month ago
Best introductury Data Analysis with R MOOC I have followed. Labs were excellent and Prof. Mahometa's teaching style is quite engaging
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Eslam Shokrey profile image
Eslam Shokrey profile image

Eslam Shokrey

8/10 starsTaking Now
4 years, 1 month ago
I Think That the content will support me to deal with data archiving data for get the output that I need through doing all the analysis that I should do.
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