Difference between revisions of "Univariate data analysis"
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Kevin Dunn (talk | contribs) (Created page with "== Learning outcomes == * The study of variability important to help answer: "what happened?" * Univariate tools such as the histogram, median, MAD, standard deviation, quarti...") |
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[[Univariate_data_analysis_(2014)|See the webpage from 2014]] | [[Univariate_data_analysis_(2014)|See the webpage from 2014]] | ||
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===Videos from 2013=== | ===Videos from 2013=== | ||
[[Univariate_data_analysis_(2013)|See the webpage from 2013]] | [[Univariate_data_analysis_(2013)|See the webpage from 2013]] | ||
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Revision as of 17:47, 2 January 2016
Learning outcomes
- The study of variability important to help answer: "what happened?"
- Univariate tools such as the histogram, median, MAD, standard deviation, quartiles will be reviewed from prior courses (as a refresher)
- The normal and t-distribution will be important in our work: what are they, how to interpret them, and use tables of these distributions
- The central limit theorem will be explained conceptually: you cannot finish a course on stats without knowing the key result from this theorem.
- Using and interpreting confidence intervals will be crucial in all the modules that follow.
Extended readings
- New Boeing planes will generate 0.5 TB of data per flight. Read about this, and other sources of data: "every piece of that plane has an internet connection, from the engines to the flaps to the landing gear".
- All students, but especially the 600-level students should read the article by Peter J. Rousseeuw, Tutorial to Robust Statistics it is easy to read, and contains so much useful content.
Resources
- Class notes 2015
- Class notes 2014
- Textbook, chapter 2
- Complete steps 10, 11, 12 and 13 of the software tutorial
- |R demo file
- Using tables of the normal distribution
Class videos from prior years
Videos from 2015
07:31 | Download video | Download captions | Script |
Videos from 2014
Videos from 2013