X-Git-Url: https://code.communitydata.science/stats_class_2020.git/blobdiff_plain/9b255d061338f1042f6661aff45f206a1b71cf70..68275101f1d127a83e2c6fd076c9929c6d3f4dd4:/psets/pset1-worked_solution.html 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