26 lines
875 B
Plaintext
26 lines
875 B
Plaintext
---
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title: "Week 6 R lecture"
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subtitle: "Statistics and statistical programming \nNorthwestern University \nMTS 525"
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author: "Aaron Shaw"
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date: "May 3, 2019"
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output: html_document
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---
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```{r setup, include=FALSE}
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knitr::opts_chunk$set(echo = TRUE)
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```
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## T-tests
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You learned the theory/concepts behind t-tests last week, so here's a brief run-down on how to use built-in functions in R to conduct them and interpret the results.
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## ANOVAs
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Analogous situation with t-tests. Here's a brief introduction to how they work in R.
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## Visualizing confidence intervals
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We spent a lot of time on confidence intervals in the past few weeks. Since they can be so useful, surely we should learn some approaches to incorporating them into data visualizations.
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## Date/time arithmetic
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Last, but not least, another wrinkle in time...or at least how to manage date-time objects in R. |