Difference between revisions of "Statistics notes - some introduction"

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You can find any pattern you want, to any level of precision you want, if you are prepared to ignore enough data  - Matt Parker
 
You can find any pattern you want, to any level of precision you want, if you are prepared to ignore enough data  - Matt Parker
 
[https://www.youtube.com/watch?v=6JwEYamjXpA&t=1658s]
 
[https://www.youtube.com/watch?v=6JwEYamjXpA&t=1658s]
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==Descriptive statistics, inferential statistics==
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The distinction between descriptive and inferential is largely that
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* inferential tries to make statements about a population based on a sample (assuming it is representative),
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* descriptive statistics describes the sample itself
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Both quantitatively describing the main features of some data,
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and many real-world statistical summaries will be a mix - roughly "this is what we observed in the sample (descriptive), and we we think it means this in the population (inferential), (and here is our sample size and how it relates to the population, etc)".
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Descriptive may do less, but in itself it is more robust - for example, you don't have to worry about sample biases such as [[selection bias]].
  
 
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[[Category:Math on data]]
 
[[Category:Math on data]]

Revision as of 13:53, 6 July 2020

This is more for overview of my own than for teaching or exercise.

Overview of the areas

Arithmetic · 'elementary mathematics' and similar concepts
Set theory, Category theory
Geometry and its relatives · Topology
Elementary algebra - Linear algebra - Abstract algebra
Calculus and analysis
Logic
Semi-sorted
 : Information theory · Number theory · Decision theory, game theory · Recreational mathematics · Dynamical systems · Unsorted or hard to sort


Math on data:

  • Statistics as a field
some introduction · areas of statistics
types of data · on random variables, distributions
Virtues and shortcomings of...
on sampling · probability
glossary · references, unsorted
Footnotes on various analyses

Other data analysis, data summarization, learning

Regression · Classification, clustering, decisions · dimensionality reduction · Optimization theory, control theory
Connectionism, neural nets · Evolutionary computing



This article/section is a stub — probably a pile of half-sorted notes, is not well-checked so may have incorrect bits. (Feel free to ignore, fix, or tell me)