Made Ridiculously Simple on Statistics @ Home
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Recent content in Made Ridiculously Simple on Statistics @ HomeHugo -- gohugo.ioen-ENstats.at.home@gmail.com (Justin and Rachel Silverman)stats.at.home@gmail.com (Justin and Rachel Silverman)(c) 2017 Justin and Rachel SilvermanThu, 12 Oct 2017 00:00:00 +0000Bayesian Decision Theory Made Ridiculously Simple
http://statsathome.com/2017/10/12/bayesian-decision-theory-made-ridiculously-simple/
Thu, 12 Oct 2017 00:00:00 +0000stats.at.home@gmail.com (Justin and Rachel Silverman)http://statsathome.com/2017/10/12/bayesian-decision-theory-made-ridiculously-simple/Framing the decision space Examples: Part 1 The other information that helps us make a decision Examples: Part 2 The Loss Function Examples: Part 3 Uncertainty Fully Worked Example: What price should I sell my used phone for? Next steps Bayesian Decision Theory is a wonderfully useful tool that provides a formalism for decision making under uncertainty. It is used in a diverse range of applications including but definitely not limited to finance for guiding investment strategies or in engineering for designing control systems.Follow-up on Error Analysis
http://statsathome.com/2017/08/02/follow-up-on-error-analysis/
Wed, 02 Aug 2017 00:00:00 +0000stats.at.home@gmail.com (Justin and Rachel Silverman)http://statsathome.com/2017/08/02/follow-up-on-error-analysis/I wanted to write a quick post responding to a question that we received about our last post (Error Analysis Made Ridiculously Simple).
Can you give an example of how to generate an estimate of the error? It’s easy enough when measuring a table, as long as your meter stick is accurate: measure 1,000 times and make an inference. But in a setting where you don’t actually know the true outcome – let’s say you are trying to model household income – I’m not sure how to generate a reasonable guess of the size of the error.Error Analysis Made Ridiculously Simple
http://statsathome.com/2017/07/21/error-analysis-made-ridiculously-simple/
Fri, 21 Jul 2017 00:00:00 +0000stats.at.home@gmail.com (Justin and Rachel Silverman)http://statsathome.com/2017/07/21/error-analysis-made-ridiculously-simple/Introduction Example 1 - Adding two measurements Example 1a - Uniform Uncertainty and Max/Min Bounds Example 1b - Gaussian Uncertainty and Standard Deviation as Bounds How to Use Simulation for Calculations Example 2 - Shipping bricks Improving Back of the Envelope Calculations More Resources Code for Plotting Introduction All measurements have uncertainty. This is not a subjective opinion but an objective fact that should never be ignored.Measure Theory Made Ridiculously Simple
http://statsathome.com/2017/06/26/measure-theory-made-ridiculously-simple/
Mon, 26 Jun 2017 00:00:00 +0000stats.at.home@gmail.com (Justin and Rachel Silverman)http://statsathome.com/2017/06/26/measure-theory-made-ridiculously-simple/During my first few years of medical school I became a big fan of the [Subject] Made Rediculously Simple book series (as in Clinical Microbiology Made Rediculously Simple). I found that the authors did a great job of simplifying the subject matter, sometimes to the point of absurdity, while getting the core concepts across in a memorable way. For some time now I have wished that similar tools were available for mathematics.