From c3ab23dc32bf58365b77cc044c6f51afa22ec5de Mon Sep 17 00:00:00 2001 From: aaronshaw Date: Tue, 29 Sep 2020 12:24:19 -0500 Subject: [PATCH] typo --- psets/pset1-worked_solution.html | 2 +- psets/pset1-worked_solution.pdf | Bin 269780 -> 269778 bytes psets/pset1-worked_solution.rmd | 2 +- 3 files changed, 2 insertions(+), 2 deletions(-) diff --git a/psets/pset1-worked_solution.html b/psets/pset1-worked_solution.html index bd80eb7..354e4e9 100644 --- a/psets/pset1-worked_solution.html +++ b/psets/pset1-worked_solution.html @@ -1803,7 +1803,7 @@ p + geom_histogram()

## Statistical questions

### SQ1

-

A compelling answer to this depends on the variable you chose. For the one I looked at in my example code (`poverty`) the data is somewhat right skewed, but not much. In this case, the mean and standard deviation should represent the central tendency and spread of the variable pretty well. If your variable was different (e.g., one of the population or income measures, it would probably be good to also examine and report the median and interquartile range. See `OpenIntro` chapter 2 for more on distinctions/reasons behind this.

+

A compelling answer to this depends on the variable you chose. For the one I looked at in my example code (`poverty`) the data is somewhat right skewed, but not much. In this case, the mean and standard deviation should represent the central tendency and spread of the variable pretty well. If your variable was different (e.g., one of the population or income measures), it would probably be good to also examine and report the median and interquartile range. See `OpenIntro` chapter 2 for more on distinctions/reasons behind this.

### SQ2

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