Chapter 12 Frequencies
12.1 Intro
Frequency tables are normally used to inspect the distribution of categorical (dichotomous, nominal or ordinal) variables.
12.1.1 Example dataset
This example uses the Rosetta Stats example dataset “pp15” (see Chapter 1 for information about the datasets and Chapter 3 for an explanation of how to load datasets).
12.1.2 Variable(s)
From this dataset, this example uses variable currentEducation_cat.
12.2 Input: jamovi
Figure 12.1: A screenshot placeholder
12.3 Input: R
There are many packages that can be used to create a frequency table. We have only presented two examples. Other packages include (but are not limited to):
-
- If you read an SPSS dataset into R, consider using the “frq” command from the “sjmisc” package. It presents both values and value labels (similar to SPSS output).
Note: To use the following commands, it is necessary to install and load the packages first (see section 2.3.2). The example dataset is stored under the name dat (see section 3).
12.3.1 rosetta package
Use the following command (this requires the rosetta package to be installed, see section 2.3.2, and the example dataset to be stored under name dat, see section 3):
To also order a barchart, use:
To order frequencies for multiple variables simultaneously, use:
12.3.2 descr and kableExtra packages
The descr package is used to run the “descriptive statistics” for the variable (in this case, a frequency table). By default, the freq command in the descr package will also create a basic bar graph. The kableExtra package can be combined with many packages to create aesthetically pleasing tables.
kableExtra::kable_styling(
knitr::kable(as.data.frame(descr::freq(dat$currentEducation_cat)),
booktabs=T, digits=2));In words:
- From the descr package, use the frequencies command for the currentEducation variable from the dataset:
(descr::freq(dat$currentEducation_cat). - To make the aesthetically pleasing output, we are going to create a kable from the kableExtra package. Kables require dataframes, so we need to turn this frequency output into a dataframe:
as.data.frame(). - Now, let’s call the kable function from the knitr package:
knitr::kable(). - And add some stylistic elements, such as (what does booktabs=T actually do?)
booktabs=Tand changing the number of decimal places to 2 digitsdigits=2. - Lastly, let’s add kablestyling to make the kable aesthetically pleasing:
kableExtra::kable_styling().
12.4 Input: SPSS GUI
First activate the dat dataset (see 2.4.1).
Figure 12.2: A screenshot placeholder
12.5 Input: SPSS Syntax
Use the following command (this requires the dat dataset to be the active dataset, see 2.4.1):
FREQ VARIABLES=currentEducation_cat.To also order a barchart, use:
FREQ VARIABLES=currentEducation_cat
/BARCHART FREQ.To order frequencies for multiple variables simultaneously, use:
FREQ VARIABLES=currentEducation_cat prevEducation_cat.12.6 Output: jamovi
Figure 12.3: A screenshot placeholder
12.7 Output: R
12.7.1 rosetta package
## Frequencies Perc.Total Perc.Valid Cumulative
## Applied 108 13.0 13.0 13.0
## Declined to answer 7 0.8 0.8 13.9
## Not studying 166 20.0 20.0 33.9
## Practical 28 3.4 3.4 37.3
## Theoretical 520 62.7 62.7 100.0
## Total valid 829 100.0 100.012.7.2 descr and kableExtra packages
12.8 Output: SPSS
Figure 12.4: A screenshot placeholder
12.9 Read more
If you would like more background on this topic, you can read more in these sources:
- Discovering Statistics with SPSS (closed access):
- Learning Statistics with R (Navarro 2018): section XXXXXXXXXX, page XXXXXXXXXX (or follow this link for the Bookdown version)