Description summarizes observed data or a phenomenon without manipulating a test variable or condition. It supports understanding new data sources, developing metrics, sizing opportunities, and informing decisions. section 3.2.1
Descriptive analysis can use quantitative or qualitative data and commonly reports:
- Central tendency, including mean, median, and mode. section 3.2.1
- Distribution measures, such as standard deviation for continuous data. section 3.2.1
- Counts and proportions for categorical data. section 3.2.1
- Trends over time, group differences, or other summaries selected after exploring the dataset. section 3.2.1
Descriptive statistics may stand alone in reports and dashboards or provide context for inferential analysis. Choose measures carefully: distribution shape affects interpretation, and omitting a statistic can change what stakeholders conclude. Descriptive results describe observed patterns but do not test an intervention. section 3.2.1 section 3.2
Rat-sighting trends
A daily dataset of rat sightings can be plotted over time, grouped by month, and summarized with monthly totals, means, and medians. Comparing the mean and median helps communicate how the reported sightings vary across months.
