Descriptive Statistics

Summarise your dataset with means, medians, standard deviations, and visualisations — the essential first step in any analysis.

Descriptive Statistics summarise the key features of a dataset — its central tendency (mean, median, mode), variability (SD, variance, IQR, range), shape (skewness, kurtosis), and distribution (histogram, box plot). Every analysis begins with descriptive statistics: they reveal data quality issues, inform test selection, and are required in every published methods section.

StatRyx computes a full descriptive statistics table for all selected variables, detecting variable types automatically. Continuous variables get mean, SD, median, IQR, min, max, skewness, and kurtosis. Categorical variables get frequencies and percentages. Histograms and box plots are generated automatically.

Choose the summary to fit the variable. For roughly symmetric continuous variables report the mean and standard deviation; for skewed variables or those with outliers, the median and interquartile range describe the typical value more honestly. For categorical variables, report counts and percentages. Always give the sample size behind each number, because missing values mean different variables can rest on different n.

When to use the Descriptive Statistics

As the first step before any inferential analysis to understand your data
When you need to report sample characteristics in a methods section or Table 1
When checking for outliers, missing values, or distributional assumptions
You need the mean and SD of each scale score to report reliability and correlations
You want frequencies and percentages for demographic variables such as gender, age group or education

When not to use it

You need to make inferences about a population from a sample — use Inferential tests (t-test, ANOVA, regression) instead
You want to know whether two groups differ — use Independent Samples t-Test or Mann-Whitney U Test instead
You want to know whether two variables are related — use Correlation Analysis instead

Worked example

Variable	n	M	SD	Median	IQR	Min	Max	Skew	Kurt
Anxiety	200	42.3	8.7	41.5	12.0	20	68	0.34	−0.21
Depression	200	18.6	5.2	18.0	7.0	7	35	0.52	0.18

How to report it (APA 7)

Descriptive statistics for the study variables are presented in Table 1. Anxiety scores had a mean of 42.3 (SD = 8.7, range: 20–68). Skewness (0.34) and kurtosis (−0.21) were within acceptable bounds for normality.

Frequently asked questions

Is descriptive statistics free on StatRyx?

Yes. You can run it without an account (3 free analyses), and a free account adds 10 more — a one-time allowance, no payment needed. Every result includes the APA 7 write-up. Paid plans (Student from $9/month) add more analyses and Word, PDF and Excel export.

Can I get descriptives by group?

Yes. Ask StatRyx to compute descriptive statistics grouped by any categorical variable and it will produce separate summaries for each group.

What is the difference between SD and IQR?

Standard deviation (SD) measures spread around the mean and is sensitive to outliers. Interquartile range (IQR, the middle 50% of data) is robust to outliers. Report SD with mean for symmetric data; IQR with median for skewed data.

How do I report descriptive statistics in APA 7?

Use M and SD in italics, rounded to two decimals for most scales: "Participants were on average 24.6 years old (SD = 4.1)." For several variables, a table with columns n, M, SD, minimum and maximum is clearer than prose.

Should I report the mean or the median?

Report the mean for roughly symmetric data and the median (with IQR) when the distribution is skewed or has outliers — income and reaction times are classic examples. When in doubt, a histogram or the skewness value shows which one represents the data better.

Run a Descriptive Statistics on your data →