Intro to Statistics

Data Science Statistics Course reco

Hi All,

(x post from data science) I'm currently learning data analysis methods using Python. I've already completed this MIT Course and would like to move on to a course that focuses a bit more on the statistics involved in data analysis.

I do this in my spare time and I would like to continue practicing Python as I learn statistics for analysis purposes. I'm hoping some of you can recommend a good online course that achieves those two goals.

As of now, I'm looking at the following and am very open to recommendations:

• Harvard - Data Science

• Stanford - Statistical Learning

Here are some fallback courses that are stats only (would rather not do a straight stats 101 course unless you strongly recommend that I do):

• Udacity - Intro to Stat

• Coursera - Intro Stats

Thanks in advance!

https://www.udacity.com/course/intro-to-statistics--st101

gl buddy

https://www.udacity.com/course/intro-to-statistics--st101

That should help with the misunderstanding you claim to have.

I'd suggest having a cursory understanding of statistics as whole (enough to recognize vocabulary and common procedures/concepts), but there's no need to get too deep into it. Nobody should expect you to be able to apply statistics off the top of your head, but they should expect that they can task you with something involving stats and you'll be able to figure it out on your own (with the help of Google, of course). I took the free Udacity Intro to Statistics course to prepare for their Data Analyst nanodegree, and that's probably the level of stats you should be comfortable with. I think I got it wrapped up in a week, to give you some perspective of timing.

As far as not knowing data analytics concepts coming into the job, I wouldn't worry about it. You're gonna be an intern. They don't expect much of you. If you interviewed for the position and they hired you, that means that you have demonstrated to them what they needed to see to feel comfortable with putting you on the job (seems obvious, but it's an important aspect). Obviously the more you know about the subject, the easier things will be and the better you'll do. But they'll provide you with everything you'll need to succeed, so studying data analytics prior to getting the job is somewhat moot. Within a few weeks, you'll most likely have the same capacity to do the job either way.

What you should focus on is the tools and technology they use. Try to figure out which languages, libraries, processes, etc. that they use (or that you'll be using) on a regular basis and brush up on those things. This doesn't end with "Python + Tableau" either. If they use git, make sure you're good with git. If they use Jira for ticket handling, make sure you understand what that is and how it works. Development teams can work with inexperienced team members, but only if they are able to follow the processes that are in place. They're going to be willing to teach you everything you need to know about data analytics once you get there, but they'll have a problem if you can't conform to their processes.

Introductory statistics

Hello!

I'm looking to learn some introductory statistics over the next couple of months, and came across 2 free courses offered by Udacity. I was wondering if anyone here has taken them. If so, would you recommend them or am I better off finding courses elsewhere?

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The courses are Intro to Statistics and Intro to Inferential Statistics

> they’re going to kill us all

Just for you, and it's free!

This was a better introduction to statistics than any book I found (they're free):

https://www.udacity.com/course/intro-to-descriptive-statistics--ud827
https://www.udacity.com/course/intro-to-inferential-statistics--ud201

Those prepared me for a master's level course in statistics so if it starts to be way more info than you need, Udacity has come out with this course since I took the ones above and it may be more useful:

https://www.udacity.com/course/intro-to-statistics--st101

There is a link on here for this course.

https://www.mathsisfun.com/data/standard-deviation.html

https://www.mathsisfun.com/data/index.html

https://www.udacity.com/course/intro-to-data-science--ud359

https://www.udacity.com/course/intro-to-descriptive-statistics--ud827

https://www.udacity.com/course/intro-to-inferential-statistics--ud201

just the free course, not the nanodegrees
https://www.udacity.com/course/intro-to-statistics--st101

https://www.youtube.com/playlist?list=PL8dPuuaLjXtNM_Y-bUAhblSAdWRnmBUcr

http://patrickjmt.com/#probability-statistics

First of all, I could recommend to study Python. Why? There are some reasons.

1.Python is the fastest growing programming language. You can use it for ML applications, data analysis, visualization, web apps, API integrations, etc.

2.It’s one of the easier languages to pick up and learn.

Below some sources that I think will be good for your self learning.
https://learnpythonthehardway.org/

https://community.modeanalytics.com/python/tutorial/pandas-dataframe/

If you haven't learnt ML before, check also these free online-courses
https://www.udacity.com/course/intro-to-machine-learning--ud120

https://www.udacity.com/course/intro-to-statistics--st101

https://www.udacity.com/course/intro-to-data-science--ud359

Hope you'll find it useful!

https://www.udacity.com/course/intro-to-statistics--st101

https://www.udacity.com/course/intro-to-descriptive-statistics--ud827

https://www.udacity.com/course/intro-to-inferential-statistics--ud201

These courses on Statistics by Udacity are nice enough for most purposes. If you finish the first one, or the other two combined you can take a look at this specialization from Coursera too.
https://www.coursera.org/specializations/mathematics-machine-learning?

It s the one I finished, because I was not as rusty on Statistics back then, and I found it amazing. I like particularly the intuitive approach they took, and not bore you till death with meaningless proofs, however, the last course on PCA is a glaring exception to this rule.