Statistics learning recommendations - Revision history

Vipul: /* =Cartoon books */

2014-06-27T22:20:40Z

=Cartoon books

← Older revision		Revision as of 22:20, 27 June 2014
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	Statistics.com offers over 110 [http://www.statistics.com/course-catalog/ statistics courses]. The courses are expensive: $500 for a 4-week long course. We don't have any inside knowledge of the quality of the courses.		Statistics.com offers over 110 [http://www.statistics.com/course-catalog/ statistics courses]. The courses are expensive: $500 for a 4-week long course. We don't have any inside knowledge of the quality of the courses.

	===Cartoon books==		===Cartoon books===

	The blog post [http://www.r-bloggers.com/the-most-comprehensive-review-of-comic-books-teaching-statistics/ The most comprehensive review of comic books teaching statistics] discusses and reviews a number of cartoon books teaching statistics. These can be ideal for many people who want to learn statistics informally or even for people who want to learn statistics formally and are looking for a way to supplement their main learning source.		The blog post [http://www.r-bloggers.com/the-most-comprehensive-review-of-comic-books-teaching-statistics/ The most comprehensive review of comic books teaching statistics] discusses and reviews a number of cartoon books teaching statistics. These can be ideal for many people who want to learn statistics informally or even for people who want to learn statistics formally and are looking for a way to supplement their main learning source.

Vipul: /* Recommendations */

2014-06-24T14:03:15Z

Recommendations

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	Statistics.com offers over 110 [http://www.statistics.com/course-catalog/ statistics courses]. The courses are expensive: $500 for a 4-week long course. We don't have any inside knowledge of the quality of the courses.		Statistics.com offers over 110 [http://www.statistics.com/course-catalog/ statistics courses]. The courses are expensive: $500 for a 4-week long course. We don't have any inside knowledge of the quality of the courses.

			===Cartoon books==

			The blog post [http://www.r-bloggers.com/the-most-comprehensive-review-of-comic-books-teaching-statistics/ The most comprehensive review of comic books teaching statistics] discusses and reviews a number of cartoon books teaching statistics. These can be ideal for many people who want to learn statistics informally or even for people who want to learn statistics formally and are looking for a way to supplement their main learning source.

Jsinick at 00:45, 18 February 2014

2014-02-18T00:45:46Z

← Older revision		Revision as of 00:45, 18 February 2014
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	Statistics is a fundamental tool in the social sciences, medical sciences, actuarial science and finance. Aside from being useful professionally, some of the basic concepts of statistics are also crucial to quantitative literacy and making sense of the world in day to day life.		Statistics is a fundamental tool in the social sciences, medical sciences, actuarial science and finance. Aside from being useful professionally, some of the basic concepts of statistics are also crucial to quantitative literacy and making sense of the world in day to day life.

	You should be warned that statistics expositions are sometimes conceptually misguided. The focus on ''frequentist statistics'' rather than ''Bayesian statistics'' is arguably an example of this, though this has been [~~disputed~~ http://lesswrong.com/lw/jne/a_fervent_defense_of_frequentist_statistics/]. It's important to learn the standard perspectives in order to understand and communicate with people who use them. However, you should be critical in your reading about the subject – if some of the material doesn't make sense, it's possible that this is because it doesn't have good justification rather than because you're misunderstanding something.		You should be warned that statistics expositions are sometimes conceptually misguided. The focus on ''frequentist statistics'' rather than ''Bayesian statistics'' is arguably an example of this, though this has been [http://lesswrong.com/lw/jne/a_fervent_defense_of_frequentist_statistics/ disputed]. It's important to learn the standard perspectives in order to understand and communicate with people who use them. However, you should be critical in your reading about the subject – if some of the material doesn't make sense, it's possible that this is because it doesn't have good justification rather than because you're misunderstanding something.

	Statistical intuition isn't the same as technical knowledge of statistical methods like factor analysis. One can have the technical knowledge without the intuition or the intuition without the technical knowledge. If you're planning on going into a line of work where statistics is used, you need to acquire the technical knowledge, but for general quantitative literacy, reading our recommendations for statistical intuition may be sufficient.		Statistical intuition isn't the same as technical knowledge of statistical methods like factor analysis. One can have the technical knowledge without the intuition or the intuition without the technical knowledge. If you're planning on going into a line of work where statistics is used, you need to acquire the technical knowledge, but for general quantitative literacy, reading our recommendations for statistical intuition may be sufficient.

Jsinick at 00:45, 18 February 2014

2014-02-18T00:45:09Z

← Older revision		Revision as of 00:45, 18 February 2014
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	Statistics is a fundamental tool in the social sciences, medical sciences, actuarial science and finance. Aside from being useful professionally, some of the basic concepts of statistics are also crucial to quantitative literacy and making sense of the world in day to day life.		Statistics is a fundamental tool in the social sciences, medical sciences, actuarial science and finance. Aside from being useful professionally, some of the basic concepts of statistics are also crucial to quantitative literacy and making sense of the world in day to day life.

	You should be warned that statistics expositions are sometimes conceptually misguided. The focus on ''frequentist statistics'' rather than ''Bayesian statistics'' is arguably an example of this. It's important to learn the standard perspectives in order to understand and communicate with people who use them. However, you should be critical in your reading about the subject – if some of the material doesn't make sense, it's possible that this is because it doesn't have good justification rather than because you're misunderstanding something.		You should be warned that statistics expositions are sometimes conceptually misguided. The focus on ''frequentist statistics'' rather than ''Bayesian statistics'' is arguably an example of this, though this has been [disputed http://lesswrong.com/lw/jne/a_fervent_defense_of_frequentist_statistics/]. It's important to learn the standard perspectives in order to understand and communicate with people who use them. However, you should be critical in your reading about the subject – if some of the material doesn't make sense, it's possible that this is because it doesn't have good justification rather than because you're misunderstanding something.

	Statistical intuition isn't the same as technical knowledge of statistical methods like factor analysis. One can have the technical knowledge without the intuition or the intuition without the technical knowledge. If you're planning on going into a line of work where statistics is used, you need to acquire the technical knowledge, but for general quantitative literacy, reading our recommendations for statistical intuition may be sufficient.		Statistical intuition isn't the same as technical knowledge of statistical methods like factor analysis. One can have the technical knowledge without the intuition or the intuition without the technical knowledge. If you're planning on going into a line of work where statistics is used, you need to acquire the technical knowledge, but for general quantitative literacy, reading our recommendations for statistical intuition may be sufficient.

Jsinick: Jsinick moved page Statistics learning resources to Statistics learning recommendations

2014-02-10T23:30:58Z

Jsinick moved page Statistics learning resources to Statistics learning recommendations

← Older revision	Revision as of 23:30, 10 February 2014
(No difference)

Jsinick at 20:44, 8 February 2014

2014-02-08T20:44:53Z

← Older revision		Revision as of 20:44, 8 February 2014
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	Statistics is a fundamental tool in the social sciences, medical sciences, actuarial science and finance. Aside from being useful professionally, some of the basic concepts of statistics are also crucial to quantitative literacy.		Statistics is a fundamental tool in the social sciences, medical sciences, actuarial science and finance. Aside from being useful professionally, some of the basic concepts of statistics are also crucial to quantitative literacy and making sense of the world in day to day life.

	You should be warned that statistics expositions are sometimes conceptually misguided. The focus on ''frequentist statistics'' rather than ''Bayesian statistics'' is arguably an example of this. It's important to learn the standard perspectives in order to understand and communicate with people who use them. However, you should be critical in your reading about the subject – if some of the material doesn't make sense, it's possible that this is because it doesn't have good justification rather than because you're misunderstanding something.		You should be warned that statistics expositions are sometimes conceptually misguided. The focus on ''frequentist statistics'' rather than ''Bayesian statistics'' is arguably an example of this. It's important to learn the standard perspectives in order to understand and communicate with people who use them. However, you should be critical in your reading about the subject – if some of the material doesn't make sense, it's possible that this is because it doesn't have good justification rather than because you're misunderstanding something.

Jsinick at 20:44, 8 February 2014

2014-02-08T20:44:26Z

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	~~== Generalities ==~~

	Statistics is a fundamental tool in the social sciences, medical sciences, actuarial science and finance. Aside from being useful professionally, some of the basic concepts of statistics are also crucial to quantitative literacy.		Statistics is a fundamental tool in the social sciences, medical sciences, actuarial science and finance. Aside from being useful professionally, some of the basic concepts of statistics are also crucial to quantitative literacy.

Jsinick at 20:44, 8 February 2014

2014-02-08T20:44:02Z

← Older revision		Revision as of 20:44, 8 February 2014
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	Statistics is a fundamental tool in the social sciences, medical sciences, actuarial science and finance. Aside from being useful professionally, some of the basic concepts of statistics are also crucial to quantitative literacy.		Statistics is a fundamental tool in the social sciences, medical sciences, actuarial science and finance. Aside from being useful professionally, some of the basic concepts of statistics are also crucial to quantitative literacy.

	~~Students~~ should be warned that statistics expositions sometimes conceptually misguided. The focus on ''frequentist statistics'' rather than ''Bayesian statistics'' is arguably an example of this. ~~However, it~~'s important to learn the standard perspectives in order to understand and communicate with people who use them.		You should be warned that statistics expositions are sometimes conceptually misguided. The focus on ''frequentist statistics'' rather than ''Bayesian statistics'' is arguably an example of this. It's important to learn the standard perspectives in order to understand and communicate with people who use them. However, you should be critical in your reading about the subject – if some of the material doesn't make sense, it's possible that this is because it doesn't have good justification rather than because you're misunderstanding something.

	Statistical intuition isn't the same as technical knowledge of ~~things~~ like ~~how to perform~~ factor analysis. One can have the technical knowledge without the intuition or the intuition without the technical knowledge. If you're planning on going into a line of work where statistics is used, you need to acquire the technical knowledge, but for general quantitative literacy, reading our recommendations for statistical intuition .		Statistical intuition isn't the same as technical knowledge of statistical methods like factor analysis. One can have the technical knowledge without the intuition or the intuition without the technical knowledge. If you're planning on going into a line of work where statistics is used, you need to acquire the technical knowledge, but for general quantitative literacy, reading our recommendations for statistical intuition may be sufficient.

	~~AP Statistics is generally regarded as unsubstantive and inadequate – students who want to build quantitative literacy should supplement the material with other materials such as those listed below~~.

	== Recommendations ==		== Recommendations ==

Jsinick at 20:40, 8 February 2014

2014-02-08T20:40:08Z

← Older revision		Revision as of 20:40, 8 February 2014
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	Statistics is a fundamental tool in the social sciences, medical sciences, actuarial science and finance. Aside from being useful professionally, some of the basic concepts of statistics are also crucial to quantitative literacy.		Statistics is a fundamental tool in the social sciences, medical sciences, actuarial science and finance. Aside from being useful professionally, some of the basic concepts of statistics are also crucial to quantitative literacy.

	Students should be warned that statistics expositions sometimes conceptually misguided. ~~Arguably the~~ focus on ''frequentist statistics'' rather than ''Bayesian statistics'' is an example of this. However, it's important to learn the standard perspectives in order to understand and communicate with people who use them.		Students should be warned that statistics expositions sometimes conceptually misguided. The focus on ''frequentist statistics'' rather than ''Bayesian statistics'' is arguably an example of this. However, it's important to learn the standard perspectives in order to understand and communicate with people who use them.

	Statistical intuition isn't the same as technical knowledge of things like how to perform factor analysis. One can have the technical knowledge without the intuition or the intuition without the technical knowledge. If you're planning on going into a line of work where statistics is used, you need to acquire the technical knowledge, but for general quantitative literacy, reading ~~the material on "~~statistical intuition ~~with real world examples" may suffice~~.		Statistical intuition isn't the same as technical knowledge of things like how to perform factor analysis. One can have the technical knowledge without the intuition or the intuition without the technical knowledge. If you're planning on going into a line of work where statistics is used, you need to acquire the technical knowledge, but for general quantitative literacy, reading our recommendations for statistical intuition .

	AP Statistics is generally regarded as unsubstantive and inadequate – students who want to build quantitative literacy should supplement the material with other materials such as those listed below.		AP Statistics is generally regarded as unsubstantive and inadequate – students who want to build quantitative literacy should supplement the material with other materials such as those listed below.
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	== Recommendations ==		== Recommendations ==

	=== Statistical intuition ~~with real world examples~~ ===		=== Statistical intuition ===

	* [http://www.amazon.com/Naked-Statistics-Stripping-Dread-Data-~~ebook/dp/B007Q6XLF2/ Naked Statistics: Stripping~~ the ~~Dread from~~ the ~~Data] by Charles Wheelan~~		These are non-technical books that illustrate the concepts of statistics with real world examples. Because they illustrate the ideas in context, helpful for building statistical intuition.

	* [http://www.amazon.com/Signal-Noise-Art-Science-Prediction-ebook/dp/B007V65R54/ The Signal and the Noise] by Nate Silver		* [http://www.amazon.com/Naked-Statistics-Stripping-Dread-Data-ebook/dp/B007Q6XLF2/ Naked Statistics: Stripping the Dread from the Data] by Charles Wheelan.

			* [http://www.amazon.com/Signal-Noise-Art-Science-Prediction-ebook/dp/B007V65R54/ The Signal and the Noise] by Nate Silver. This book is organized around the theme of predicting the future.

			* [http://www.amazon.com/The-Lady-Tasting-Tea-Revolutionized/dp/0805071342 The Lady Tasting Tea: How Statistics Revolutionized Science in the Twentieth Century] by David Salsburg. This provides an early history of statistics.

	=== Frequentist approach textbook ===		=== Frequentist approach textbook ===
	[http://www.amazon.com/Statistics-Plain-English-Third-Timothy-ebook/dp/B004RM9VSY/ Statistics in Plain English] by Timothy C. Urdan is a lucid book that's only 200 pages long. It's somewhat terse and may not give enough examples. No exercises.

	[http://www.amazon.com/Statistics-For-Dummies-Deborah-Rumsey/dp/0470911085/ Statistics for Dummies], and [http://www.amazon.com/Statistics-For-Dummies-Deborah-Rumsey/dp/0470911085/ Statistics II for Dummies] offer a more leisurely exposition. [http://www.amazon.com/Statistics-Workbook-Dummies-Deborah-Rumsey/dp/0764584669/ Statistics Workbook for Dummies] offers exercises.		The most commonly taught approach to statistics is the ''frequentist'' approach.

			* [http://www.amazon.com/Statistics-Plain-English-Third-Timothy-ebook/dp/B004RM9VSY/ Statistics in Plain English] by Timothy C. Urdan is a lucid book that covers a lot of material in only 200 pages. It's somewhat terse and some readers may find it to be short on examples.
			* [http://www.amazon.com/Statistics-For-Dummies-Deborah-Rumsey/dp/0470911085/ Statistics for Dummies], and [http://www.amazon.com/Statistics-For-Dummies-Deborah-Rumsey/dp/0470911085/ Statistics II for Dummies] offer a more leisurely exposition. [http://www.amazon.com/Statistics-Workbook-Dummies-Deborah-Rumsey/dp/0764584669/ Statistics Workbook for Dummies] offers exercises.

	=== Bayesian statistics ===		=== Bayesian statistics ===

	Chapter 8 of [http://www.amazon.com/Signal-Noise-Art-Science-Prediction-ebook/dp/B007V65R54/ The Signal and the Noise] by Nate Silver gives ~~some~~ history of Bayesian statistics and an exposition of the basics of the subject. ~~(Silver's book is well-worth skimming in entirety for developing statistical intuition.)~~		''Bayesian statistics'' is thought by many people to be a superior alternative to frequentist statistics.

			Chapter 8 of [http://www.amazon.com/Signal-Noise-Art-Science-Prediction-ebook/dp/B007V65R54/ The Signal and the Noise] by Nate Silver gives the history of Bayesian statistics and an exposition of the basics of the subject.

	Some blog posts		Some blog posts that overlap with the content of Silver's book but that the reader may find helpful for slightly different perspectives are:

	* [http://lesswrong.com/lw/774/a_history_of_bayes_theorem/ A History of Bayes' Theorem] by Luke Muehlhauser		* [http://lesswrong.com/lw/774/a_history_of_bayes_theorem/ A History of Bayes' Theorem] by Luke Muehlhauser.
	* [http://yudkowsky.net/rational/bayes An Intuitive Explanation of Bayes' Theorem] by Eliezer Yudkowsky.		* [http://yudkowsky.net/rational/bayes An Intuitive Explanation of Bayes' Theorem] by Eliezer Yudkowsky.
	* [http://lesswrong.com/lw/2b0/bayes_theorem_illustrated_my_way/ Bayes' Theorem Illustrated (My Way)] by Komponisto.		* [http://lesswrong.com/lw/2b0/bayes_theorem_illustrated_my_way/ Bayes' Theorem Illustrated (My Way)] by Komponisto.

	==== Programming ~~and Bayesian~~ statistics ====		For a full technical introduction to Bayesian statistics, [http://www.amazon.com/Introduction-Bayesian-Statistics-William-Bolstad-ebook/dp/B00D8XUJA2 Introduction to Bayesian Statistics] by William Bolstad may be helpful, but the book is very expensive.

			==== Programming statistics ====

	~~Good if~~ you ~~want~~ to ~~actually do~~ statistical ~~analysis. Good for becoming more familiar with programming.~~		If you enjoy programming, are looking to learn programming, or will be implementing statistical algorithms in your work, these books may be good choices:

	* [http://www.amazon.com/Discovering-Statistics-Using-Andy-Field-ebook/dp/B00HPZ4VVM/ Discovering Statistics Using R] by Andy Field, Jeremy Miles and Zoe Field.		* [http://www.amazon.com/Discovering-Statistics-Using-Andy-Field-ebook/dp/B00HPZ4VVM/ Discovering Statistics Using R] by Andy Field, Jeremy Miles and Zoe Field.
	* [http://www.~~amazon~~.com/~~Think-Bayes-Allen-B-Downey-ebook/dp/B00F5BS96Q~~/ Think Bayes: Bayesian Statistics Made Simple] by Allen Downey teaches statistics through Python programming.		* [http://www.greenteapress.com/thinkbayes/thinkbayes.pdf Think Bayes: Bayesian Statistics Made Simple] by Allen Downey teaches statistics through Python programming.
	* [http://www.amazon.com/Doing-Bayesian-Data-Analysis-Tutorial/dp/0123814855/ Doing Bayesian Data Analysis: A Tutorial with R and BUGS] by John Kruschke.		* [http://www.amazon.com/Doing-Bayesian-Data-Analysis-Tutorial/dp/0123814855/ Doing Bayesian Data Analysis: A Tutorial with R and BUGS] by John Kruschke.

	~~==== Data analysis ====~~

	~~We don't have subject matter knowledge, but these books are very highly reviewed on Amazon.~~

	* [http://www.amazon.com/Doing-Data-Science-Straight-Frontline/dp/1449358659 Doing Data Science: Straight Talk from the Frontline] by Cathy O'Neil and Rachel Schutt.
	* [http://www.amazon.com/Data-Science-Business-data-analytic-thinking/dp/1449361323/ Data Science for Business: What you need to know about data mining and data-analytic thinking] by Foster Provost and Tom Fawcett.
	* [http://www.amazon.com/Data-Smart-Science-Transform-Information/dp/111866146X/ Data Smart: Using Data Science to Transform Information into Insight] by John Foreman

	=== Online classes ===		=== Online classes ===
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	* [https://www.coursera.org/ Coursera] offers ~45 statistics courses. Their offerings include [https://www.coursera.org/course/stats1 Statistics One], an introductory course.		* [https://www.coursera.org/ Coursera] offers ~45 statistics courses. Their offerings include [https://www.coursera.org/course/stats1 Statistics One], an introductory course.
	* [https://www.edx.org/ edX] offers ~20 statistics courses, including [https://www.edx.org/course/uc-berkeleyx/uc-berkeleyx-stat2-1x-introduction-1138 Introduction to Statistics: Descriptive Statistics], [https://www.edx.org/course/uc-berkeleyx/uc-berkeleyx-stat2-3x-introduction-1533 Introduction to Statistics: Inference] and [https://www.edx.org/course/uc-berkeleyx/uc-berkeleyx-stat2-2x-introduction-1534 Introduction to Statistics: Probability], which are associated with UC Berkeley.		* [https://www.edx.org/ edX] offers ~20 statistics courses, including [https://www.edx.org/course/uc-berkeleyx/uc-berkeleyx-stat2-1x-introduction-1138 Introduction to Statistics: Descriptive Statistics], [https://www.edx.org/course/uc-berkeleyx/uc-berkeleyx-stat2-3x-introduction-1533 Introduction to Statistics: Inference] and [https://www.edx.org/course/uc-berkeleyx/uc-berkeleyx-stat2-2x-introduction-1534 Introduction to Statistics: Probability], which are associated with UC Berkeley.
	* [https://www.udacity.com/ Udacity] offers [https://www.udacity.com/course/st101 Intro to Statistics] and [https://www.udacity.com/course/st095 Statistics.		* [https://www.udacity.com/ Udacity] offers [https://www.udacity.com/course/st101 Intro to Statistics] and [https://www.udacity.com/course/st095 Statistics].
	* [http://ocw.mit.edu/index.htm MIT OCW] offers an [http://ocw.mit.edu/courses/mathematics/ math courses] that include "Introduction to Probability and Statistics" and "Statistics for Applications."		* [http://ocw.mit.edu/index.htm MIT OCW] offers an [http://ocw.mit.edu/courses/mathematics/ math courses] that include "Introduction to Probability and Statistics" and "Statistics for Applications."
	* Carnegie Mellon University's [http://oli.cmu.edu/ Open Learning Initiative] offers [https://oli.cmu.edu/jcourse/webui/guest/join.do?section=probstat a course on probability and statistics].		* Carnegie Mellon University's [http://oli.cmu.edu/ Open Learning Initiative] offers [https://oli.cmu.edu/jcourse/webui/guest/join.do?section=probstat a course on probability and statistics].

	Statistics.com offers over 110 [http://www.statistics.com/course-catalog/ statistics courses]. The courses are expensive: $500 for a 4-week long course. We don't have any inside knowledge of the quality of the courses.		Statistics.com offers over 110 [http://www.statistics.com/course-catalog/ statistics courses]. The courses are expensive: $500 for a 4-week long course. We don't have any inside knowledge of the quality of the courses.

Jsinick: /* Recommendations */

2014-02-08T20:15:44Z

Recommendations

← Older revision		Revision as of 20:15, 8 February 2014
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	* [https://www.edx.org/ edX] offers ~20 statistics courses, including [https://www.edx.org/course/uc-berkeleyx/uc-berkeleyx-stat2-1x-introduction-1138 Introduction to Statistics: Descriptive Statistics], [https://www.edx.org/course/uc-berkeleyx/uc-berkeleyx-stat2-3x-introduction-1533 Introduction to Statistics: Inference] and [https://www.edx.org/course/uc-berkeleyx/uc-berkeleyx-stat2-2x-introduction-1534 Introduction to Statistics: Probability], which are associated with UC Berkeley.		* [https://www.edx.org/ edX] offers ~20 statistics courses, including [https://www.edx.org/course/uc-berkeleyx/uc-berkeleyx-stat2-1x-introduction-1138 Introduction to Statistics: Descriptive Statistics], [https://www.edx.org/course/uc-berkeleyx/uc-berkeleyx-stat2-3x-introduction-1533 Introduction to Statistics: Inference] and [https://www.edx.org/course/uc-berkeleyx/uc-berkeleyx-stat2-2x-introduction-1534 Introduction to Statistics: Probability], which are associated with UC Berkeley.
	* [https://www.udacity.com/ Udacity] offers [https://www.udacity.com/course/st101 Intro to Statistics] and [https://www.udacity.com/course/st095 Statistics.		* [https://www.udacity.com/ Udacity] offers [https://www.udacity.com/course/st101 Intro to Statistics] and [https://www.udacity.com/course/st095 Statistics.
	* [~~MIT OCW~~ http://ocw.mit.edu/index.htm] offers an [http://ocw.mit.edu/courses/mathematics/ math courses] that include "Introduction to Probability and Statistics" and "Statistics for Applications."		* [http://ocw.mit.edu/index.htm MIT OCW] offers an [http://ocw.mit.edu/courses/mathematics/ math courses] that include "Introduction to Probability and Statistics" and "Statistics for Applications."
	* Carnegie Mellon University's [http://oli.cmu.edu/ Open Learning Initiative] offers [https://oli.cmu.edu/jcourse/webui/guest/join.do?section=probstat a course on probability and statistics].		* Carnegie Mellon University's [http://oli.cmu.edu/ Open Learning Initiative] offers [https://oli.cmu.edu/jcourse/webui/guest/join.do?section=probstat a course on probability and statistics].

	Statistics.com offers over 110 [http://www.statistics.com/course-catalog/ statistics courses]. The courses are expensive: $500 for a 4-week long course. We don't have any inside knowledge of the quality of the courses.		Statistics.com offers over 110 [http://www.statistics.com/course-catalog/ statistics courses]. The courses are expensive: $500 for a 4-week long course. We don't have any inside knowledge of the quality of the courses.