Statistics and R

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23996 reviews

Course Description

We will learn the basics of statistical inference in order to understand and compute p-values and confidence intervals, all while analyzing data with R. We provide R programming examples in a way that will help make the connection between concepts and implementation. Problem sets requiring R programming will be used to test understanding and ability to implement basic data analyses. We will use visualization techniques to explore new data sets and determine the most appropriate approach. We will describe robust statistical techniques as alternatives when data do not fit assumptions required by the standard approaches. By using R scripts to analyze data, you will learn the basics of conducting reproducible research.

Given the diversity in educational background of our students we have divided the series into seven parts. You can take the entire series or individual courses that interest you. If you are a statistician you should con...

We will learn the basics of statistical inference in order to understand and compute p-values and confidence intervals, all while analyzing data with R. We provide R programming examples in a way that will help make the connection between concepts and implementation. Problem sets requiring R programming will be used to test understanding and ability to implement basic data analyses. We will use visualization techniques to explore new data sets and determine the most appropriate approach. We will describe robust statistical techniques as alternatives when data do not fit assumptions required by the standard approaches. By using R scripts to analyze data, you will learn the basics of conducting reproducible research.

Given the diversity in educational background of our students we have divided the series into seven parts. You can take the entire series or individual courses that interest you. If you are a statistician you should consider skipping the first two or three courses, similarly, if you are biologists you should consider skipping some of the introductory biology lectures. Note that the statistics and programming aspects of the class ramp up in difficulty relatively quickly across the first three courses. By the third course will be teaching advanced statistical concepts such as hierarchical models and by the fourth advanced software engineering skills, such as parallel computing and reproducible research concepts.

These courses make up 2 XSeries and are self-paced:

PH525.1x: Statistics and R for the Life Sciences

PH525.2x: Introduction to Linear Models and Matrix Algebra

PH525.3x: Statistical Inference and Modeling for High-throughput Experiments

PH525.4x: High-Dimensional Data Analysis

PH525.5x: Introduction to Bioconductor: annotation and analysis of genomes and genomic assays 

PH525.6x: High-performance computing for reproducible genomics

PH525.7x: Case studies in functional genomics


This class was supported in part by NIH grant R25GM114818.

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Reviews 7/10 stars
13 Reviews for Statistics and R

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Florian S. profile image
Florian S. profile image

Florian S.

2/10 starsTaking Now
2 years, 9 months ago
This course is a complete mess. -The exercises are out of order, a lot of stuff is asked in exercises way before it is expressed in the videos. -A lot of exercise questions are presented in a pretty bad and wide way, often it´s just guessing what they want you to to. Thats probably why they give you 5 tries for every exercise.... -Mr. Rafael Irizarry often mentions wrong stuff like "CLT tells us that tstat is approximately normal with mean 0 (the null hypothesis) and SD 1 (we divided by its SE).", thats not true. -It seems like nobody checks the discussion board, questions based on vague exercise questions stay almost all the time unanswered (since 2 Month for example). Is this Harvard quality education?! Don´t even bother to do the whole "Life Science"-Programm, it´s not worth the money and will only frustrate you. There are way better courses out there which teach you R and Statistics.
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Michael Massengill profile image
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Michael Massengill

1/10 starsCompleted
3 years ago
I'll start with the content of this course as that was the primary source of frustration for me. -course work was out of order. ()is where it seems to me they should have gone week 1 is right where it should be week 2 (3) was far more difficult than it needed to be due to being out of place week 3 (4) built on the previous week so not as difficult week 4 (2) contains concepts and code needed for the remaining weeks in addition to this some statistical concepts and R code is explained in the lecture immediately after the worksheet that you are graded on knowledge of it. -some questions were wrong in some of the exercises answers that your solutions were compared to where wrong because a value given in the exercise was off enough to break the solution -vague and misleading questions questions often refer to previous exercises which is not uncommon or even a problem the problem here is that the exercise being referred to is not name... I'll start with the content of this course as that was the primary source of frustration for me. -course work was out of order. ()is where it seems to me they should have gone week 1 is right where it should be week 2 (3) was far more difficult than it needed to be due to being out of place week 3 (4) built on the previous week so not as difficult week 4 (2) contains concepts and code needed for the remaining weeks in addition to this some statistical concepts and R code is explained in the lecture immediately after the worksheet that you are graded on knowledge of it. -some questions were wrong in some of the exercises answers that your solutions were compared to where wrong because a value given in the exercise was off enough to break the solution -vague and misleading questions questions often refer to previous exercises which is not uncommon or even a problem the problem here is that the exercise being referred to is not named and so must be assumed in the majority of instances. -omission of necessary code even taking into account the order of lessons issues I found I spent far more time researching R code on google than I should have considering R is part of this course. Ok the worst bit is over now on to the Instructor Rafael Irizarry is the primary instructor for this course and I truly did not find any real fault with his presentation in his lectures other than what is covered in my content section. Michael Love has a grand total of 1 lecture in this course and does a good job of explaining his material. so if you search for courses based on instructors Rafael Irizarry is who you can expect. My conclusion is this course can fix most of its issues by reordering everything that it currently contains and including a bit more time in translating normal formula to code and back (which would cover some of the missing code bits) If you take this course for credit I have 3 bits of advice 1 watch every video in the course before even a single exercise. 2 search discussions for every question before you attempt answering. 3 store all code you use. this may be obvious to some of you and is good advice for most courses but it is more important for this course. Thank you for taking the time to read this review
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VYASAMURTHY MANTENA profile image
VYASAMURTHY MANTENA profile image

VYASAMURTHY MANTENA

5/10 starsTaking Now
3 years ago
SIR, Certificate cost li'l bit high please ensure this srvice, Sir It’s wonder millions of students from all around the world opt for online degree programs or take at least one college course through an online platform. Online learning has to be the greatest revolution in contemporary education. It made a huge change in the system and opened great opportunities for everyone who wants to learn something.Sir you know that The advantages of online learning that lead many students to opt for online platforms when they want to earn a degree or certificate. The best thing about online learning is that you can learn in a relaxed manner even if you don’t want to get certified. thank you sir ...
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Shah G profile image
Shah G profile image

Shah G

8/10 starsCompleted
3 years, 1 month ago
the course contents, without any exaggeration, are well designed and good learning experience for beginners in R language. I found it very helpful but it need to be clearly discussed R commands. Need some more focus on Monte Carlo simulation, P-value Power function etc. Overall course is best.
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Virgil Brown profile image
Virgil Brown profile image

Virgil Brown

2/10 starsTaking Now
3 years, 1 month ago
This course leaves a lot to be desired. The videos are rambling and skip over the details of how to use R code to work with the data. Similarly, the mathematical concepts are only discussed in a cursory manner before you are challenged in the exercises. Ultimately, you will need to seek resources outside of the course to learn the both. I guess you get what you pay for...
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David Liu profile image
David Liu profile image

David Liu

4/10 starsTaking Now
3 years, 1 month ago
I have to say this course is not well designed and . I have learned this basic statistic before but wanted to use this course as a review. The slides are basically to empty. After every 5 min of slide then we got some exercise that is overly simple (both in terms of programming and the statistics behind it). In some cases, some important concept are not well defined in the slide, such as t statistics and p value. I don't like the fact that we have to find some essential R function by ourselves. Just spent 10 to 20 minutes explaining the relevant R functions, things will go much smoother.
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Ilir Sheraj profile image
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Ilir Sheraj

10/10 starsTaking Now
3 years, 2 months ago
I could not finish the whole course last time so i decided to enroll once again. It is very helpful though the programming part is a bit hard for those with no background in R. Still i think its worth a try because the instructors have prepared a very useful textbook and very nice online sources in GitHub.
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Eric Cheng profile image
Eric Cheng profile image

Eric Cheng

8/10 starsCompleted
3 years, 5 months ago
Personally, I think this course is for people with a basic background in statistics and R programming. It would be challenging for people with no background at all because you are expected to know statistical theories. I was taking stats in school when I took this course, and it definitely helped me apply R programming to statistical analysis.
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Gavin Sowa profile image
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Gavin Sowa

6/10 starsCompleted
3 years, 5 months ago
I'm not exactly sure what to make of this series. Will it teach you R? Probably not, but it will motivate (frustrate) you to find better resources (I recommend Hadley Wickham's book on R). Will it teach you the relevant math? Again, probably not for the same reasons. It does encourage you to to think about data,but instead of teaching you the skills that you want it teaches you of your own ignorance so you search for better material. Ironically, this is the process that people on stack overflow seem to recommend for learning data science. I'm not sure if that was by design.
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student

10/10 starsCompleted
3 years, 8 months ago
Solid free resource for an introduction to stats and R for data analysis of sample data. Nice to have the instructor step through the code in the examples, though sometimes this could be broken down further. Found it helpful to refer to the textbook available free online.
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Batyr Nuryyev profile image
Batyr Nuryyev profile image

Batyr Nuryyev

8/10 starsTaking Now
3 years, 8 months ago
This course is one of the most interesting I've ever taken so far (online). Instructors explain in a super clear way. Good job!
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XUE YU profile image
XUE YU profile image

XUE YU

8/10 starsCompleted
3 years, 10 months ago
It is very useful for me especially the last part about the bad figures. I am writing a paper now. So it is good to know how to process data and make a good figure.
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kuljeet singh profile image
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kuljeet singh

8/10 starsTaking Now
4 years ago
They are calm and giving lecturers in approachable way.So it is very usfull to those students want to explore their carrier in molecular biology.Without data analyzing you cannot interpreted their results.it is also very good for those researcher who wants to publish their work and want to understand data genomics.
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