Chapter 11 Descriptives
11.1 Intro
The term ‘descriptives’ is typically used to refer to a set of measures summarizing a distribution, such as central tendency and spread measures.
11.1.1 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).
11.1.2 Variable(s)
From this dataset, this example uses variables xtcUseDoseHigh
, highDose_intention
, highDose_attitude
(all three numeric variables) and hasJob_bi
(a dichotomous factor, i.e. a categorical variable).
11.2 Input: jamovi

Figure 11.1: Opening the “Exploration” menu in jamovi.
11.3 Input: R
11.3.1 R: base
Use the following command:
11.3.2 R: Rosetta
Use the following command:
rosetta::descr(
dat,
items = c(
"xtcUseDoseHigh",
"highDose_intention",
"highDose_attitude",
"hasJob_bi"
),
histogram = TRUE,
boxplot = TRUE
);
When ordering descriptives for a single variable (and in version 0.3.2 of the rosetta
package, also for multiple variables), you can finetune which descriptives you get by passing TRUE
or FALSE
for arguments mean
, meanCI
, median
, mode
, var
, sd
, se
, min
, max
, q1
, q3
, IQR
, skewness
, kurtosis
, dip
, totalN
, missingN
, and validN
.
In addition, you can order histograms (or bar charts, for factors) and box plots (for numeric variables only) by passing histogram=TRUE
and boxplot=TRUE
, respectively.
If you omit the items
argument, you get descriptives for all variables in the dataframe; and if you don’t pass a dataframe, but a single variable, you will just get the descriptives for that variable.
11.4 Input: SPSS
11.4.1 SPSS: GUI
First activate the pp15
dataset by clicking on it (see 2.4.1).

Figure 11.2: Opening the “descriptives menu” in SPSS
Then select the variables of interest.

Figure 11.3: Selection of variables of interest
11.4.2 SPSS: Syntax
Use the following command (this requires the dat
dataset to be the active dataset, see 2.4.1):
DESCRIPTIVES VARIABLES=xtcUseDoseHigh highDose_intention highDose_attitude hasJob_bi
/STATISTICS=MEAN STDDEV MIN MAX.
11.5 Output: jamovi

Figure 11.4: The produced descriptives output in jamovi
11.6 Output: R
11.6.1 R: rosetta
11.6.1.1 Descriptives for variables in data frame pp15
mean | meanCI | median | mode | var | sd | min | max | skewness | kurtosis | dip | totalN | missingN | validN | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
xtcUseDoseHigh | 208.35 | [193.2; 223.5] | 180.0 | 200 | 17000.69 | 130.39 | 25.0 | 880.0 | 1.84 | 4.74 | 0.06 | 829 | 542 | 287 |
highDose_intention | 2.37 | [2.22; 2.51] | 2.0 | 2 | 2.17 | 1.47 | 0.5 | 15.0 | 3.14 | 18.41 | 0.09 | 829 | 431 | 398 |
highDose_attitude | 3.64 | [3.52; 3.76] | 3.8 | 4 | 1.16 | 1.08 | 1.0 | 6.4 | -0.43 | -0.05 | 0.04 | 829 | 525 | 304 |
11.6.1.1.1 Frequencies for hasJob_bi
Frequencies | Perc.Total | Perc.Valid | Cumulative | |
---|---|---|---|---|
No | 81 | 9.8 | 21.1 | 21.1 |
Yes | 302 | 36.4 | 78.9 | 100.0 |
Total valid | 383 | 46.2 | 100.0 | |
NA (missing) | 446 | 53.8 | ||
Total | 829 | 100.0 |
11.6.1.1.2 Histograms for variables in data frame pp15

Figure 11.5: Histograms for variables in data frame pp15
11.6.1.1.3 Boxplots for variables in data frame pp15

Figure 11.6: Boxplots for variables in data frame pp15
11.7 Output: SPSS

Figure 11.7: The descriptives produced in SPSS.
11.8 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)