biplot_with_correlation: Plots a biplot of two variables and gives details about their...
In benmarwick/au13uwgeoarchlab: Analysing and visualising geoarchaeology data

Description Usage Arguments Details Value See Also Examples

Useful if you want to show how two variables interact. This function assumes you have already run the function get_data. The numbers on the axes are the minimum, lower-hinge, median, upper-hinge and maximum of the data. This is Tukey's five number summary. This plot has a very high data:ink ratio, without, I think, looking too ultra- minimalist.

1	biplot_with_correlation(my_data, var1, var2, ...)

`my_data`	string, the data resulting from the `get_data` function
`var1`	string, a variable in the data frame resulting from the `get_data` function
`var2`	string, another variable in the data frame resulting from the `get_data` function

The function also calculates the correlation coeffient and displays it on the x-axis in the form of r = some number. This shows the probability value of the null hypothesis (that the computed correlation is due to random processes that we don't care about). This value will help us test the hypothesis that the overall slope of the linear regression is 0 (ie. there is no relationship between the two variables). A line with slope 0 (ie. r = 0 or very close to zero) is horizontal, which means that variable 1 does not depend on variable 2 at all.

A correlation value (r) is considered to be interesting only when the p value is less than 0.05 (or for some people, 0.01). This is just an arbitrary convention. if itt's greater. If the p-value is greater than 0.05, then the correlation is most likely due to chance and not suggestive of anything interesting. So before you get excited about a high r value, do check that you also have a sufficiently low p-value.

a biplot and summary statistics of the correlation between the two variables

get_data