A data set containing information about the sizes of Norway rat skulls in the pellets of Scandinavian eagle-owls is available in the ratskull.csv file (you may have come across this before). The data comprise a column of rat skull sizes (measured in grams) and a column of codes indicating the season when a particular skull sample was taken. These data were collected in order to evaluate whether there is a difference between sizes of rats eaten in summer and winter. That is, we want to know if there is a statistically significant difference between the mean rat skull sizes in the winter and summer samples.
Download the ratskull.csv file from Google Classroom and place it in your working directory (this is the location you set at the beginning of each R session). Read the data in ratskull.csv into R.
Start by looking at the data — both visually and in terms of its descriptive statistics:
Inspection. Use the View function and dplyr function glimpse to visually inspect the raw data. What are the names given to rat skull size variable and the season indicator variable? What values does the season indicator variable take?
Descriptive statistics. Use the appropriate dplyr functions (group_by and summarise) to calculate the sample size, sample mean and standard deviation of each sample.
Graphs. Use ggplot2 to construct a pair of dot plots, one above the other, to summarise the winter and summer skull size distributions. HINT: you will need to use geom_dotplot and the facet_wrap functions to do this.
Using the dot plots, and the descriptive statistics, conduct an informal evaluation of the assumptions of the t-test.
Question. Do you feel the data conform acceptably to the assumptions? If not, make sure you can explain why.
Use the R t.test function to compare the skull sizes from each sex.
Question. Prepare a concise but complete conclusion summarising the results of the test. Is this what you expected from looking at the distributions of data in the two samples?
Question. Suggest two possible biological reasons for the result you observe.
We are now going to look at prey choice between male and female eagle owls. You have seen that the prey of eagle owls can be established by examination of the pellets containing the undigested remains of their prey. In the eagle owl study the diets of the male and female of a pair were studied by examination of the pellets collected from beneath their roosts (fortunately, an individual tends to use the same roosting site, and individuals tend not to roost together). The numbers of all prey types found in the pellets were recorded.
These data are in the file eagles.csv Read these data into R and inspect them to ensure you understand how they are organised. Once you understand the data, make a bar plot to summarise the important patterns.
Determine whether there is any evidence of differences in the diets of the male and female eagle owls.
Question. What do you conclude? If there is an effect, what might account for the result?