Quantitative/ Analysis
Descriptive statistics
See the distribution before testing it
Descriptive statistics summarise observed data using counts, proportions, location, spread and distributional displays. Means and standard deviations answer different questions from medians and interquartile ranges. Numerical summaries should accompany plots and explicit denominators, particularly when missing values, skewness, outliers or unequal group sizes make one average misleading.
WHEN IT FITS
Use first to understand a dataset, describe the participants or firms observed, and choose defensible subsequent analyses. Preserve measurement units and distinguish the sample from the target population.
Strengths
- Reveals errors and distributional features early
- Communicates magnitudes in familiar units
Limitations
- Averages can hide subgroups and extreme observations
- Sample summaries alone do not justify population inference
Know the boundary
A descriptive table does not show that an observed difference generalises or is caused by a treatment.
USED ACROSS
Banking & financeBusiness & MBAPsychologyComputer scienceEducation