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Free Coursera/Princeton online Statistics course starts this week

user9876

Senior Member
Messages
4,556
Yes, and it's free.


Oh, and it's based on a statistical language 'S' (clever, eh) that I think is used to underpin commercial packages. But the developers of S went on to build R.

R is an open source version of S or S Plus but I'm not sure its by the same developers. I think it will become increasingly important as there is a lot of work to integrate it into Hadoop which is an alternative version of a database which handles massive data sets.
 
Messages
15,786
Woohoo, just finished watching the lectures and doing the quiz for the first week.

The lectures were pretty easy, nicely broken into 10-15 minute chunks, and each with a clear and concrete example making them easy to follow and remember.

Using the R software was a bit difficult ... and for some reason just installing the file was harder than learning how to use it. I blame brain fog :p

The worst part was the quiz, which implied that multi-part answers were required for some questions, but really just wanted the very last part. It would say "make a vector and blah blah blah", but didn't want us to input the vector into the answer box, just the part after "And then what would you type to do this final bit?" Looks like that drove everyone batty, so it wasn't just my ME brain :thumbsup:
 

Snow Leopard

Hibernating
Messages
5,902
Location
South Australia
Yes, and it's free.

The bad news is it's R, a command line programme, which has a steep learning curve. ]

What are the differences? Do people use SPSS because they are simply more familiar with it? Some people say that SPSS is easier to use for common stuff, using spreadsheet like data structures, whereas R is more powerful but more difficult. Would you agree?
 

Simon

Senior Member
Messages
3,789
Location
Monmouth, UK
What are the differences? Do people use SPSS because they are simply more familiar with it? Some people say that SPSS is easier to use for common stuff, using spreadsheet like data structures, whereas R is more powerful but more difficult. Would you agree?
Main difference is R is free and open source, but harder-to-use due to clunky command-line interface.
As to more powerful, I am in no position to judge myself as I have only used R. However, according to Andrew Conway, the psychology prof taking the course who formerly used the likes of SPSS, they are much the same in power/capabilities, wtih the exception that R has potential for cooler (output) graphics (if you know what you are doing), like this graph of facebook interactions:

facebook-social-graph.jpg


Also, new techniques eg machine code learning are likely to be available on R before commercial packages because R is progammeable so new techniques can be added. The code for these new functions, once checked, are then made available as add-ons to anyone.
 

Graham

Senior Moment
Messages
5,188
Location
Sussex, UK
Dear Graham, my mathematician friend teaches statistics at UW Madison, yes I have terrible brain fog from sleep apnea also and perhaps NAFLD- so ME is a swelling of the brain? I started to have less fog after starting NAC, phosphitadyl choline, but am exhausted on this asv ventilator

Does this course teach you how to do statistical data processing with any sort of professional software, eg SPSS etc?

Yes, as Simon says it is R. The steep learning curve is largely when you know what you want the software to do (shall we say swap rows with columns), but have no idea what instruction to use, have no idea what the technical term is for it, so really struggle to find it. Then when you find the command, it is easy to use.
 

Bob

Senior Member
Messages
16,455
Location
England (south coast)
I've just been looking at the edx.org website which offers free online courses from Harvard, MIT, and Berkeley.
I came across a course called Fundamentals of Clinical Trials, and thought I'd flag it up, in case it piques anyone's interest. (The course started on 14 Oct 2013, and I don't know how that affects enrolment.)
It does require some previous stats knowledge: "Prerequisites: Background in biostatistics and epidemiology equivalent to the content of PH207X." ('PH207X' refers to an old course which can be found here. This isn't a current course, so I don't think it can be enrolled upon currently.)


Fundamentals of Clinical Trials
Clinical trials play a pivotal role in evidence-based medicine. This course will discuss the design, conduct, analysis, and interpretation of Phase I-IV clinical studies.
ABOUT THIS COURSE
This course will provide an introduction to the scientific, statistical, and ethical aspects of clinical trials research. Topics include the design, implementation, and analysis of trials, including first-in-human studies (dose-finding, safety, proof of concept, and Phase I), Phase II, Phase III, and Phase IV studies. All aspects of the development of a study protocol will be addressed, including criteria for the selection of participants, treatments, and endpoints, randomization procedures, sample size determination, data analysis, and study interpretation. The ethical issues that arise at each phase of therapy development will be explored.

This course contains 12 modules. The modules will be released Monday of each week, with the exception of some holiday weeks. Most students should plan to spend 4 – 6 hours on each module. Students will have until February 14, 2014 to earn a HarvardX certificate.

https://www.edx.org/course/harvard-university/hsph-hms214x/fundamentals-clinical-trials/941

Prerequisite PH207x:
Health in Numbers: Quantitative Methods in Clinical & Public Health Research
PH207x is the online adaptation of material from the Harvard School of Public Health's classes in epidemiology and biostatistics.
ABOUT THIS COURSE

Quantitative Methods in Clinical and Public Health Research is the online adaptation of material from the Harvard School of Public Health's classes in epidemiology and biostatistics. Principled investigations to monitor and thus improve the health of individuals are firmly based on a sound understanding of modern quantitative methods. This involves the ability to discover patterns and extract knowledge from health data on a sample of individuals and then to infer, with measured uncertainty, the unobserved population characteristics. This course will address this need by covering the principles of biostatistics and epidemiology used for public health and clinical research. These include outcomes measurement, measures of associations between outcomes and their determinants, study design options, bias and confounding, probability and diagnostic tests, confidence intervals and hypothesis testing, power and sample size determinations, life tables and survival methods, regression methods (both, linear and logistic), and sample survey techniques. Students will analyze sample data sets to acquire knowledge of appropriate computer software. By the end of the course the successful student should have attained a sound understanding of these methods and a solid foundation for further study.

https://www.edx.org/course/harvard-university/ph207x/health-numbers-quantitative/354
 
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Battery Muncher

Senior Member
Messages
620
This looks fantastic, and I'm thinking of doing this next year (circumstances - and health! - permitting). We could really use more people with statistical knowledge!

How is this year's cohort getting on? Is the pace manageable? How helpful are the materials etc.? Do you feel you're getting much out of it?
 
Messages
15,786
This looks fantastic, and I'm thinking of doing this next year (circumstances - and health! - permitting). We could really use more people with statistical knowledge!

How is this year's cohort getting on? Is the pace manageable? How helpful are the materials etc.? Do you feel you're getting much out of it?
I did well for the first half, then had a couple weeks with a lot of appointments, events, and crashes. But I plan to get back into it (albeit not on the usual timeline) now that I'm doing better. It's important to remember that there's no need to keep pace with the course, since all materials (including quizzes) are available at any time, and there's no credit or anything for keeping up with the schedule anyhow.

I've found it fairly helpful for understanding statistics presented in papers. It's mostly aimed at producing those statistical analyses, and requires learning a little bit of programming to do it. It will be immensely helpful if I ever want to perform statistical analyses for whatever reason, but the course is a lot more than is necessary if you just want to understand statistics.