Statistics with R

Online Stats Course

Hi r/statistics,

With the plethora of options for statistics courses online, which would you guys recommend for someone who hasn't taken a stats course in four years? I've been doing the Khan Academy Statistics and Probability, but I wasn't too sure if this would be the best resource.

Looking at past threads, I've seen people mention Duke's Statistics with R Specialization, These R-Bloggers videos, and a few others.

I want to learn statistics to potentially switch careers into data science. So, I'm leaning towards the Duke course, but I don't know if that covers the basics or not and a refresher is more than needed for me.

In the end, I know doing any of them would be better than doing nothing, but I just want to hear other people's opinions. Thanks in advance!

Intermediate statistics course (with lecture videos and free textbook) from the Technical University of Denmark (DTU)

I've been struggling to find an online mathematical statistics course with video lectures, since the majority of online statistics courses don't use much math (such as the Duke's Statistics with R course or Bekeley's Statistics 21. The only true mathematical statistics course with video lectures that could find was CMU's 36-705, but the video lectures' quality is quite poor.

However, today I accidentally covered a statistics course that partially met my criteria. It's the Introduction to Statistics course from the Technical University of Denmark. What I like about this course is:

1) The textbook is free!

2) Video lectures are available (under the 'Podcast' tab of the course website)

3) Homework and solutions are available, as well as exams going back a few years (again, with solutions!)

4) Most formulas have mathematical derivations (though it might not be quite as rigorous as an standard mathematical statistics course e.g. calculus was not present much, if at all)

5) Combine both probability and statistics so someone who wants to refresh both topics or learn them both for e.g. machine learning could accomplish quickly in one course.

I have taken the Duke's statistics courses on Coursera, but will use this course to strengthen my probability and stats knowledge before I embark on a real Machine Learning course (I'm looking at CMU's 10-701 by Tom Mitchell). Hope you guys find this course useful as I do!

Is there any good statistics specialization (MOOC, certification) with Python?

I heard great stuff about Duke's R Statistics specialization. Is there any similar program with Python?

Here's Duke's R Statistics Specialization https://www.coursera.org/specializations/statistics

Moving from Software Engineer to Data Scientist

Hello Everyone,

I've been thinking about switching from my current career of doing mostly web development to becoming more of a date scientist.

I don't know exactly how I'd like to do this but I imagine it would involved some sort of online course (https://www.coursera.org/specializations/statistics - this is a paid course but I'm okay with a free one if we can find a good free one) and a good buddy to partner up with to help move things along.

I'd like to the person I team up with to already be a software developer of some sort so there isn't that gap to bridge. I've been working for roughly 3ish years in industry, so anyone with similar or more experience works for me.

I'd expect us to do this course fairly independently, check in on each other, talk about concepts on google hangout. Those types of things.

If you are interested please let me know below and give me a little bit of your background if you can :)

(my background- Grew up in Connecticut, went to a small liberal arts school for English but ended up getting a BA in CS instead. Then did a web bootcamp in san francisco, got a job there, and have been working and living in SF ever since.)

How's my plan to self teach myself to become a Data Scientist?

So I studied something completely irrelevant in college (History) and landed a pretty good job a few years out of college in a major company as a BI Analyst. Even though it's a big company, the department I work in runs more like a start up, so I get to wear all sorts of different hats and manage everything in analytics.

I've been here a year and my plan is to use this job as my playground to learn and experiment. When I first started, everyone was just using Excel and doing everything really manually, like joining data sets using vlookup, remove duplicates, and then sumifs (uh yeah, you can imagine how long this took).

Thanks to coursera and online tutorials (classes are expensed by the company which makes this even sweeter), I self taught myself SQL and began implementing and using RDMBS. I first used Access and then am slowly learning and using SQL Server 2014 (free version). It's definitely saved me a lot of time on reporting and my boss has praised me for being innovative and proactive.

I'm currently taking a class on data visualization and communication with Tableau on coursera. Once I'm finished with that, I'm planning on taking courses on stats and R, specifically this: https://www.coursera.org/specializations/statistics

Do you think after I take all these classes, coupled with practical work application on my job, I can essentially become a self taught data scientist in a matter of 2-3 years of total experience? It kinda of amazes me that I can literally dive into this profession without any formal training - I mean I'm just taking online classes and applying what I learn to my job.

I'm also learning some of the data back end stuff, in part because I have to. This entails like setting up SQL Server, developing an ETL process, etc. Do you think this is something I should focus on? I should note that the only reason I feel I need to learn this is because my current job doesn't have any engineering resources on my team to implement it for me. I figured I would just do it myself, but I know if I were to move on to another company with dedicated support, there usually would be staff that does all this for me.

https://www.coursera.org/specializations/statistics This one is fantastic

I learned a ton from taking the Coursera's statistics courses from Duke University. It's a whole specialization, but you can take individual classes. The textbook they used is free for the ebook and is very well written.

just started two days ago
https://www.edx.org/course/the-analytics-edge

What you'll learn
An applied understanding of many different analytics methods, including linear regression, logistic regression, CART, clustering, and data visualization
How to implement all of these methods in R
* An applied understanding of mathematical optimization and how to solve optimization models in spreadsheet software

there's also
https://www.coursera.org/specializations/statistics

https://www.edx.org/professional-certificate/harvardx-data-science

https://trevorhastie.github.io/ISLR/

https://www.coursera.org/specializations/statistics

Coursera's Statistics with R Specialization - learn statistics and get your hands dirty with R on the way. You can audit each course for free, but if you want access to graded assignments you'll have to pay up. If you have a CS degree you should already know basic Calculus and Linear Algebra right? At least when I attended college, my school's CS degree required 4 semesters of Calculus and 1 semester of Linear Algebra.

Working professional here, should I pursue certification: Statistics with R specialization ?

I am a BI developer with 3 years of working experience. I have worked on ETL and Reporting. I think the next logical step for advancing in my career is Data Science. I have a fairly good understanding of business. My goal is to work in techno-business role in near future. I do not have any technical certifications and I think getting certified in Statistics will be beneficial no matter what course my career takes. I have an intermediate understanding of R and can work my through problems. Currently, planning to take the Statistics with R Specialization Statistics with R Specialization . Just want to know your views on the course syllabus and I am open to suggestions/ alternatives to these certification. Also, you can recommend any other technical certification that will be a plus for my goal.

I was actually deciding between this one and the Duke Statistics with R course https://www.coursera.org/specializations/statistics?

I have done the Statistics with R specialization on Coursera. As a multi-course specialization, it may be more extensive than what you're looking for, but it does exactly what you asked for, and it is very good.

Koi online Statistics course suggest karega?

Duke ka mila hai ek: https://www.coursera.org/specializations/statistics

Kisi ne try kia hai kya?

The best stats basics course IMO is the Statistics with R Specialization.

The instructor, Mine Çetinkaya-Rundel explains concepts in a very simple and easy language, that you won't forget the concepts at all. If you're not keen on using R, you can skip some of the videos/assignments for now, although learning R would be very helpful in the long run.

https://www.coursera.org/specializations/statistics

A more advanced one is Mathematical Biostatistics Bootcamp 1 & 2. Both very good, but requires a bit more mathematical literacy. Would recommend not skimping on the maths.

R programming to be more precise. Check out these courses by the same instructor : https://www.coursera.org/specializations/statistics

Statistics with R | Coursera

Basic Statistics Class or Bayesian Statistics Class

I'm finishing Analytics Edge on EdX in the next week or two and I am looking to focus on learning statistics. I failed statistics twice in college before passing. I know the bare basics like mean, median mode and standard deviation. I don't really understand how to interpret P values, Z scores and I see things I'm unfamiliar with floating around like T tests, Kurtosis, Bayesian Inference etc. My question is, for my next course should I look for a straight Introduction to Statistics Course and then a Bayesian Statistics Course later or go straight into a Bayesian Course? Any recommendations for MOOCs. I was looking at this set of courses from Coursera https://www.coursera.org/specializations/statistics . Has anyone taken it? Any reviews/thoughts?

there's a companion course on coursera which uses the open intro stats textbook for additional material and exercises. i never formally studied stats, so I don't know how complete the course is and all of that, but i thought it was a fun primer on stats with accompanying markdown files in R.

A pleasure! I found myself in the same situation before knowing R.

I didn’t have any background in statistics. I’ve worked some times with SPSS but nothing relevant, I’m pretty much still learning by myself.

Regardless, having some background in statistics sure is helpful, but nothing you can’t learn by yourself by investing some time into it.

There are also courses on the internet, such as in coursera, that teach statistics with R. I haven’t taken it but I’m looking forward to it.

[Q][E] Would really love some advice on some online courses I can take to supplement my learning

Hello! I'm a returning statistics major who hasn't done any sort of stats in a very long time. I swapped back and forth in my major and landed back into statistics so here I am. I remember taking a probability course and statistics course which was really math and proof heavy. I then took a regression course. This was all about two years ago and I barely remember anything to be honest. I'm starting my upper year courses now and I'm quite lost to say the least.

As for the upper year courses, I'm taking a course called "Categorical Data Analysis" which seems to be my hardest upcoming course. We're doing a bit of proofs but we're mostly working with different distributions like poisson and such. The description for the course says we cover this.

> Statistical models for categorical data. Contingency tables, generalized linear models, logistic regression, multinomial responses, logit models for nominal responses, log-linear models for two-way tables, three-way tables and higher dimensions, models for matched pairs, repeated categorical response data, correlated and clustered responses. Statistical analyses using SAS or R.

I then have another course called multivariate analysis. This seems okay so far since we've mostly been doing linear algebra review but now we're getting into discussing the multivariate normal distribution and I'm already feeling like I'll be left behind. The description for this course is as follows

> Linear algebra for statistics. Multivariate distributions, the multivariate normal and some associated distribution theory. Multivariate regression analysis. Canonical correlation analysis. Principal components analysis. Factor analysis. Cluster and discriminant analysis. Multidimensional scaling. Instruction in the use of SAS.

I'm also taking another applied data collection course which seems like it shouldn't be too hard.

I really do enjoy the field of statistics so I guess I'm just trying to re-learn it well because I feel like I didn't learn it properly the first time (I still wonder how I passed), but at the same time, I wish to hopefully cover things I'll be going over in class since I'd like to do well in those courses even if I will be going back and re-learning everything!

So, do you guys have any recommendations of any online courses I can take to help me? I prefer video lectures to just straight books as I feel like I absorb information better if that makes sense. Having someone explain it to me just feels better I guess.

I've looked around and I have come up with two options. First being Statistics 110 (tho I heard this doesn't go over statistical inference, which even though I don't remember what it is, sounds like something I've done in a few of my classes) and the second being the Duke statistics with R specialization.

Any recommendations will be welcomed, thanks so much!

I took the Coursera course, 'Statistics with R' at https://www.coursera.org/specializations/statistics. Besides the introduction to R, the statistics review was useful too.

Although I took Linear Algebra and multi-variate calc many years ago, I plan on doing this before applying to OMSCS: https://www.coursera.org/specializations/mathematics-machine-learning and https://www.coursera.org/specializations/statistics

I recommend the Coursera Specialization, Statistics with R by Duke University. The Specialization is based on the book OpenIntro Statistics. Both the specializations and the book are free.

The Specialization

The book

If you want the certificate for the course but can't pay, you can ask for the financial aid.

Coursera statistics with a focus on R

https://www.coursera.org/specializations/statistics?action=enroll

Or, if you're pretty comfortable with stats already, I would use Khan academy or a similar resource to learn python and then you can Google the code for R suite and tweak it to your own liking, because 8/10 times someone has already done it

https://www.coursera.org/specializations/statistics

So you want to write a story but don't really have any idea of the main part of what you'd be writing about, and you only have the bare bones of a plot?

> Probability deals with predicting the likelihood of future events, while statistics involves the analysis of the frequency of past events. Probability is primarily a theoretical branch of mathematics, which studies the consequences of mathematical definitions while statistics is primarily an applied branch of mathematics, which tries to make sense of observations in the real world.

I recommend taking a few months and working through:

• https://online.stanford.edu/course/probability-and-statistics-self-paced
• https://www.class-central.com/mooc/2309/udacity-intro-to-descriptive-statistics
• https://www.class-central.com/mooc/3048/edx-soc120x-i-heart-stats-learning-to-love-statistics
• https://www.class-central.com/mooc/2244/edx-ut-7-01x-foundations-of-data-analysis and the part 2
• https://www.coursera.org/learn/basic-statistics?siteID=SAyYsTvLiGQ-PK0cKnVLZVCAlLaxRqNOkg
• https://www.coursera.org/specializations/statistics?siteID=SAyYsTvLiGQ-EcjFmBMJm4FDuljkbzcc_g
• https://www.class-central.com/mooc/1496/edx-6-041x-introduction-to-probability-the-science-of-uncertainty

You're going to need to understand statistics/probability to figure out the plot, because you're going to want the protagonist to discover/notice things that tie back in with the math.

Now you can handwave most of this, but you're still going to need at least a bare plot: the characters (protagonists, antagonists, and NPC's), the climax points, setting, etc.

Johns Hopkins university has excellent courses on r and data analysis on Coursera. It is one of the oldest running courses on the platform and they explain both the application and the math behind it. They also have public health specializations.

https://www.coursera.org/jhu

For a deep dive in statistics I suggest dukes statistic inference specialization.

https://www.coursera.org/specializations/statistics#howItWorks

Hey, thanks! For DS and bioinformatics I think you will find this one interesting:

Statistics with R (Coursera Specialization from Duke University) - Dr. Rundel teaches statistics decently.

and then maybe this one:

Mastering Software Development in R (Coursera Specialization from Johns Hopkins University)

Python and R are the two dominant languages in DS, so be prepared to learn both eventually!

http://faculty.marshall.usc.edu/gareth-james/

https://www.coursera.org/specializations/statistics

I did my initial research for finding a statistical lecture with mix of R and so far I heard good things about this 2. Just want to know if whom should I prioritized first. Or is there any other else better than these 2?

Thank you!

I keep saying this but the Statistics course at Duke/Coursera is really really good. You will get a great background in data analysis and a great background using R (along with markdown).

For the SQL side? Take an easier route and do something like W3Schools.

Links:

W3Schools: https://www.w3schools.com/sql/

Duke/Coursera: https://www.coursera.org/specializations/statistics

Difficult to say how you'd handle the time commitment without knowing more about your educational background, your motivation for taking the course, or what you do professionally. From the course description:

> In this Specialization, you will learn to analyze and visualize data in R and create 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.

> You 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, suitable for applying for statistical analysis or data scientist positions.

https://www.coursera.org/specializations/statistics

They advertise the course as a beginner level course requiring no prior experience. In my view this course would be approachable to anyone with a moderate-to-strong background in math (read: has taken linear algebra or higher level courses in the last 3-5 years), preferably with an intro to mathematical statistics somewhere in their prior training. Familiarity with frequentist or bayesian inference would be a bonus. An intro level exposure to any programming language is strongly encouraged.

If you have at least one of the things mentioned before, I think you'll be fine. The posted requirement is 3 hours per week. You can probably do it in 2-5 hours depending on your comfort level with portions of the material and your familiarity with the R programming language.

If you can afford the enrollment fee and you're interested in the certificate for building a portfolio of data analyses, it's going to be a good course. Duke is home to a top 20 department in statistics, and I'm sure they will give exceptional instruction in the course.

This program - Statistics with R. There are 5 courses total, professor is quite engaging. https://www.coursera.org/specializations/statistics

Buscando cursos de estadística para data analysis y machine learning, vi que por acá recomendaban mucho éste: https://www.coursera.org/specializations/statistics. Yo lo empecé y, al menos el primer módulo, se me hizo muy ameno. Si lo tomás en modo "auditar" es gratuito, aunque no se pueden enviar los test para ser revisados

You can choose between the Statistics with R Specialization at Coursera, Statistics in Medicine at Lagunita Stanford or Foundations of Data Analysis 1 and Foundations of Data Analysis 2 at Edx

Confused on learning route

I know this question has been posted numerous times, but please bear with me.

There are way to many options out there that I don't know which route to take. I am currently majoring in Computer Science, and want to go into Data Analysis. I have taken one statistics course at my college, but don't have the options to continue on with that in school.

Right now, I am signed up for Python for Data Science and Machine Learning bootcamp, which I definitely want to finish. But it seems like it teaches you more about the tools of data science and less about the thought process and other techniques.

There's like an infinite amount of resources out there, and I'm confused about which one to pursue. For example:

• Dataquest.io
• Foundations of Data Analysis edX Part 1 Part 2
• The Analysts Edge edX
• Statistics with R Specialization Coursera
• Machine Learning by Andrew Ng Coursera

And so many more.

I graduate in May of 2018, so I'm trying to be marketable by December to give me a chance to find an actual full time job by next summer. I'm excited about Data Science and Machine Learning, so motivation is not an issue.

Does anybody have any suggestions on which of these I should pursue, or other options? I like the dataquest.io route because it's hands on, but it's also pricey. I also figure I should learn something with R since I have experience with Python under my belt already.

My thoughts are to take a statistics course to complement the bootcamp I'm taking.

What do you guys think?

there is a statistics course on R made by duke university, you can watch it for free by auditing it

https://www.coursera.org/specializations/statistics

statistics with python by Michigan university

https://www.coursera.org/specializations/statistics-with-python

I've seen that there are a few ongoing R Langauge MOOCs going on at EdX and Coursera recently. I can't vouch for any of them, but it might help for you to audit one of them for free.

Edx:

https://www.edx.org/course/statistics-and-r

Coursera:

https://www.coursera.org/learn/r-programming?specialization=data-science-foundations-r

And another one on Coursera:

https://www.coursera.org/specializations/statistics

Statistics with R specialization

Data Camp

Learning statistics with R

Have you seen this:

- first 2 courses in this program (Python): https://www.edx.org/micromasters/data-science

- this program (statistics and R): https://www.coursera.org/specializations/statistics

I can't comment on how good they are, and this will also depend on your requirements and prior knowledge. But it could be interesting for you to have a look!

First of all, thanks for the fantastic write up. Secondly, you are correct, I want to firmly grasp the subject, as I've heard from a lot of people in the corporate sector that econometrics are a must. I'll addres your points as you've laid them out.

(1) Excellent, I've been looking at this course, but got scared it was too advanced for me. I'll definetely dig into it if it's my level.

(2) Another excellent recommendation, I'll go through it as they state it's pretty basic. If anyone is reading this later, here's the link to their edx course: https://www.edx.org/course/probability-the-science-of-uncertainty-and-data-0

Since we're on this subject,what do you think of this course: https://www.coursera.org/specializations/statistics

Since it teaches R as well, I'm inclined to check it out. It seems even lighter than the MIT one, so maybe I should go through it first or is that a bad idea?

(3) I had it on my first year, same as stat, but yeah, I need a refresher, so I will look at more MIT courses!

Once again, thanks for answering, it means a ton to me!

I would practise being sure of what you're getting before spending > $10 on anything.

On the specialisation website, under "How It Works", the very first sentence says:
A Coursera Specialization is a series of courses that helps you master a skill.

If you scroll a little further down to "Courses", the headline says:
There are 5 Courses in this Specialization
and then proceeds to list the 5 courses, which you can click for further info.

At this point, it would be reasonable to look up further information if you're unfamiliar with some stuff (for example, Specializations, on the Coursera Help Center).

I'm currently going through MIT OCW math courses and a statistics course on coursera and I'm finding them really well done

Single Variable Calculus

Multi Varibale Calculus

Linear Algebra

Probability

Statistics

I took the John Hopkins Data Science specialization a while ago when it first came out; it was in R (think it still is), but I thought it was pretty good. I honestly prefer R to Python personally, but it's much less popular in industry now. The course focuses a lot more on tooling then theory, but it's good to get you started

I took the Deep Learning specialization (deeplearning.ai) last year, it's good for learning the fundamentals of neural networks, it's in Python.

https://www.coursera.org/learn/machine-learning? is generally people's go to for an intro to machine learning; it's in Octave/Matlab which is unfortunate, but if you don't mind jumping around languages it teaches the fundamentals quite well

https://www.coursera.org/specializations/statistics is pretty good, I only took the first course but it's really good if you have a weak statistics background or just want to see if you have any gaps to fill in

There's some courses from U. of Ill. that are a part of there DS masters on their; I took the cloud computing one, it's basically distributed systems, honestly a lot more useful for a software engineer then for a data scientist but IMO it was a great class

I'm sure there's more, but those are the ones that I've tried or finished. It's just an awesome platform

I took an earlier version of this MOOC, which I can highly recommend. It's put on by Duke University, starts with statistics basics and builds towards statistical learning methods using R. It was an excellent way to learn statistics/probability fundamentals in a practical way for me. Looks like the first two courses in this specialization are the content from the course I took? (scroll down to see all courses).

https://www.coursera.org/specializations/statistics

Here are some free ebooks that I have from the course, both have the instructor as an author, I'm not sure which or both are directly used in the course(s).

https://www.openintro.org/book/os/

https://www.openintro.org/download.php?file=isrs1_tablet

Your going to have a ton of theoretical math involved in a higher quality BS in statistics. In general it will include Real Analysis, Linear Algebra, Measure Theory, and Probability/Statistics for math majors. In these classes you will do about 80-100% of your course work doing mathematical proofs, where you logically prove the foundations of calculus, probability, statistics, as well as what mathematical systems are and why they work.

If you really enjoy this kind of deep theoretical thought, then look up a curriculum for a BS in stats and just look for the courses or books online. If you want to just learn the basics of applied stats (pretty much what you would use in industry), just take some applied stats courses. https://www.coursera.org/specializations/statistics is a pretty good course, can take it for free.

Also, these books are great:

Intro to statistical learning: https://faculty.marshall.usc.edu/gareth-james/ISL/

Elements of Statistical Learning: https://web.stanford.edu/\~hastie/ElemStatLearn/

The intro is much more accessible, still really deep. Elements is more along the lines of what someone with a classic training in mathematics/statistics would learm

On the contrary to what people on willbell thread are saying, I have a BTech in Electronics and Communication engineering. I have learnt some coding languages like C, C++, python, along with coding languages in ECE like assembly, Arduino. I have used them to develop codecs and for audio signal processing. I think learning languages gives you an understanding of how you can use a machine to do what you desire.

So you can start with a MOOC like Chuck Severance's Programming for everybody. You can even audit it. Or you can use Youtube series like Bucky Robert's Python Programming Tutorials (OLD version, Python 2) or Python 3.4 Programming Tutorials. You can use this to learn python, in general, to do whatever you want. And then " you learn one statistic concept and then see how you can program the concept in r or python ".

Or if you want to learn statistics-intensive way, you can find MOOCs like

a. https://www.coursera.org/learn/python-data-analysis

b. https://www.coursera.org/specializations/statistics

c. https://www.edx.org/course/statistics-and-r

d. https://www.edx.org/course/probability-and-statistics-in-data-science-using-python-0

Now I am doing BSc in Statistics, Maths and Computer Science. (programming then statistics) order has benefitted me. I could easily learn other languages like Maxima or Scilab. I also have the option of implementing the code in a language I already know.

I personally feel "it's easier to teach a software developer statistics than it is to teach a statistician to program" - google or Amazon, as I see some of the old stats professors and research scholars at my University are devoid of programming skills and find it hard sometimes.

I think you're looking for guides/tutorials/lessons on R. It's because RStudio, most basically, is an alternative GUI for R.

There exist numerous resources on R on the web.

Quick-R is a good start point to learn R. https://www.statmethods.net/

A free course on R @Datacamp: https://www.datacamp.com/courses/free-introduction-to-r

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Some courses @Coursera

R Programming course: https://www.coursera.org/learn/r-programming

Statistics for R: https://www.coursera.org/specializations/statistics

Other R courses: https://www.coursera.org/courses?query=R

​

And as you know, tons of video lectures @Youtube: https://www.youtube.com/results?search_query=r+programming

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Here is R documentation including many manuals:https://www.r-project.org/other-docs.html

20 Free Online Books to Learn R and Data Science: https://cmdlinetips.com/2018/01/free-online-resources-books-to-learn-r-and-data-science/

Learn R : 12 Free Books and Online Resources: http://ucanalytics.com/blogs/learn-r-12-books-and-online-resources/

R related twitter accounts: https://twitter.com/sarptas/lists/r