You have learned about how to set up a script, locate and download data, explore that data and summarise the data. Via dplyr, you now have several tools such as select, slice, filter and mutate that allow you to access data. You know several tools such as group_by, summarise and %>% that allow easy summarisation of your data.
Here is your assignment. It involves working with a new data set on cattle weight gain as a function of the diet they are fed (grains) and vitamin supplements to their diet. The data are called growth.csv and are in the folder you’ve downloaded from us with all of the data.
Prepare a NEW script and populate it with appropriate annotation.
Download and explore with str or glimpse or tbl_df the growth.csv data.
Estimate by hand or in your head, the total number of average weights you can calculate from these data.
Use dplyr tools to calcuate the mean, standard error and sample size of cattle weight gain in each combination of diet and supplement
Use dplyr to obtain only the means for the barley diet.
EXTRA credit. Use the function quantile() and filter to get raw weight values that are in the top 10% of all weights in the data set.