Ch. 9 | Exercise 4

# Chapter 9 | Exercise 4

Which register has the greatest proportion of metaphoric uses of on? The smallest? The frequencies in the VU Amsterdam Metaphor Corpus are shown in Table 9.1.

Table 9.1. Metaphoric and non-metaphoric uses of on in different registers
Academic Conversations Fiction News
Metaphoric 255 163 112 205
Non-metaphoric 37 96 121 77

Test if there is a significant association between the register and (non)-metaphoricity. Visualize the data in a mosaic and association plot.

First, create a table in R with all frequencies:

```> met <- c(255, 163, 112, 205) > nonmet <- c(37, 96, 121, 77) > on <- rbind(met, nonmet) > colnames(on) <- c('acad', 'conv', 'fic', 'news') > on acad conv fic news met 255 163 112 205 nonmet 37 96 121 77 ```

To compare the proportions of metaphoric and non-metaphoric uses in four registers, you can use the following code:

```> prop.table(on, 2) acad conv fic news met 0.8732877 0.6293436 0.4806867 0.7269504 nonmet 0.1267123 0.3706564 0.5193133 0.2730496 ```

The academic register has the greatest proportion of metaphoric uses (0.87). Fiction has the lowest proportion (0.48).

Now we should test if the variables are associated:

```> chisq.test(on) Pearson's Chi-squared test data: on X-squared = 99.7487, df = 3, p-value < 2.2e-16 ```

The p-value is almost zero, so the null hypothesis of no association can be safely discarded. To check the contribution of each cell to the result, check the residuals:

```> chisq.test(on)\$residuals acad conv fic news met 3.78232 -1.165787 -3.838463 0.7575156 nonmet -5.63622 1.737196 5.719882 -1.1288110 ```

The positive and negative values of the residuals indicate the same differences that we have observed. To visualize the residuals, use the `mosaic()` and `assoc()` functions in the `vcd` package:

```> library(vcd) > mosaic(on, shade = T) > assoc(on, shade = T) ```