do you see any indication that there may be a difference between the two types of clients

INSTRUCTIONS TO CANDIDATES

ANSWER ALL QUESTIONS

(Already did 1-4, need help on the rest) 1. Download the file Wholesale customers data.csv from http://archive.ics.uci.edu/ml/machine-learning-databases/00292/ Read the data into a dataframe called ws.df. Get the summary information for ws.df to familiarize yourself with the various vectors included in the data frame. Attach ws.df to the search path. 2. Draw a histogram of the spending on fresh produce. Make sure that the histogram displays the relative frequency on the y-axis and add a smoothed-line. 3. Draw a boxplot of milk purchases separated out by channel. Do you see any indication that there may be a difference between the two types of clients? 4. Draw a scatterplot of the milk spending vs. deli spending, using a log scale for both axes. Do you see any indication that there might be a pattern there? 5. You can use the following commands to create a column labeled CR that contains 6 possible values: 11, 12, 13, 21, 22, 23. The first digit corresponds to the channel number and the second digit corresponds to the region number. As such, CR divides the clients into categories by both region and channel. The commands then add this column to the dataframe ws.df and then group the fresh produce and the milk purchase data by CR. For each group, the average sales in the fresh produce and milk categories are saved in dataframes FbyCR and MbyCR, respectively. CR <- Channel*10+Region wws.df <- data.frame(ws.df,CR) FbyCR <- aggregate( Fresh~CR,wws.df,mean ) MbyCR <- aggregate( Milk~CR,wws.df,mean ) Issue these commands and draw barplots of the fresh produce sales for the six groups. Draw another barplot, this time for milk sales. Can you compare the average fresh produce and milk spending in the six groups? What insights do you gain from the barplots? 6. Instead of two separate barplots, draw a barplot that stacks the average fresh produce and milk sales on top of one another. Repeat the same exercise, but put the fresh produce and milk bars next to one another. 7. Draw a dotplot that includes both average fresh produce and milk spending for each value in CR, sorted by the amount spent. 8. Draw the histogram and the boxplot from (2) and (3) using ggplot. 9. Draw the scatterplot from (4) using ggplot. 10. Draw the barplot and the dotplot from (5) and (7) using ggplot.

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