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en:learning:schools:s01:worksheets:ba-ws-07-1

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 en:learning:schools:s01:worksheets:ba-ws-07-1 [2015/09/22 16:22] en:learning:schools:s01:worksheets:ba-ws-07-1 [2015/09/22 16:22] (current) Line 1: Line 1: + ====== W07-1 Descriptive data set properties ====== + This worksheet summarizes descriptive statistic functions which can be used to describe the properties of a data set. After completing this worksheet you should know how to use basic descriptive statistic functions and produce box whisker plots. + + ===== Things you need for this worksheet ===== + * {{section>​en:​resources:​templates:​tools#​R environment&​inline}} + * {{section>​en:​resources:​templates:​tools#​R studio&​inline}} + * your script and data from [[en:​learning:​schools:​s01:​worksheets:​ba-ws-06-1|W06-1 Leave-one-out validation]] + ===== Learning log assignments ===== + + :!: This time, the following analysis is build on top of your script from [[en:​learning:​schools:​s01:​worksheets:​ba-ws-06-1|W06-1]]. Please copy your script "​W06-1.R",​ rename the copy to "​W07-1.R"​ and use it for the programming tasks of this worksheet. + + :-\ Please figure out the functions for some general descriptive statistics: mean, median, standard deviation, maximum and minimum. Let's try those on the observed animal activity data set. + + :-\ Let's compare the descriptive values with the predicted values of the animal activity from [[en:​learning:​schools:​s01:​worksheets:​ba-ws-06-1|W06-1]]. ​ + + While those values give us a good impression of the differences between the observed and predicted animal activity data set, a visualization might be more intuitive. + + :-\ Please visualize the data set properties of the observed and predicted animal activity using a boxplot (e.g. function boxplot()). ​ + + :-\ Please identify the outliers by computing a scatter plot first and then starting the identify() function. Now you can click on a point of the plot to get the meta information for it. + + To terminate the identify() function, just hit Escape​ +