Data Secrets: Smart Research for Real Results

In Blog 22, let’s see how to create mathematical expressions for your graph. Mathematical expressions on graphs are made possible through expression(paste()) and substitute(). If you need mathematical expressions as axis labels, switch off the default axes and include Greek symbols by writing them out in English. You can create…

Today we see how to set up multiple graphs on the same page. We use the syntax par(mfrow=(A,B)), where A refers to the number of rows and B to the number of columns (and where each cell will hold a single graph). This syntax sets up a plotting environment of…

The [su_label]Rsample[/su_label] package contains functions that allow different types of resampling (e.g. cross-validation, bootstrap, etc.). The data structure in which resampling data is stored is a data frame and is very convenient for further work. You can read more about the [su_label]Rsample[/su_label] package on the official package page: https://github.com/tidymodels/rsample. The…

You can re-code an entire vector or array at once. To illustrate, let’s set up a vector that has missing values. A <- c(3, 2, NA, 5, 3, 7, NA, NA, 5, 2, 6) A We can re-code all missing values by another number (such as zero) as follows: A[…

SPSS has the Count Values within Cases option, but R does not have an equivalent function. Here are two functions that you might find helpful, each of which counts values within cases inside a rectangular array. For example, you might have a dataset consisting of responses to a questionnaire involving…

Test for the existence of particular values using the any() and all() commands Create a vector b: b <- c(7, 2, 4, 3, -1, -2, 3, 3, 6, 8, 12, 7, 3) b Use the function any() to see if there is any element in b equal -4 and less…

Counting elements in a dataset Combining the length() and which() commands gives a handy method of counting elements that meet particular criteria. b <- c(7, 2, 4, 3, -1, -2, 3, 3, 6, 8, 12, 7, 3) b Let’s count the 3s in the vector b. count3 <- length(which(b ==…

In Part 15, we saw how to create a simple Generalised Linear Model on binary data using the glm() command. We continue with the same glm (modelling the vs variable on the weight and engine displacement) on the same data set – the mtcars dataset – which is built into…

In Part 15, let’s see how to create simple Generalised Linear Models in R. Ordinary Least Squares regression provides linear models of continuous variables. However, much data of interest to statisticians and researchers are not continuous and so other methods must be used to create useful predictive models. The glm()…

In Part 14, let’s see how to create pie charts in R. Let’s create a simple pie chart using the pie() command. As always, we set up a vector of numbers and then we plot them. B <- c(2, 4, 5, 7, 12, 14, 16) Create a simple pie chart….