Module 1 · Descriptive Statistics · Topic 2
Qualitative vs Quantitative. Qualitative (categorical) data describes qualities or categories, like color or brand. Quantitative (numerical) data represents amounts or counts, like height or test scores.
Levels of Measurement. There are four levels: Nominal (categories with no order, e.g., eye color), Ordinal (ordered categories, e.g., letter grades), Interval (equal spacing but no true zero, e.g., temperature in Celsius), and Ratio (equal spacing with a true zero, e.g., weight).
Discrete vs Continuous. Discrete data can only take specific values, often counts (e.g., number of siblings). Continuous data can take any value within a range (e.g., height of 5.743 feet).
xbar = sum(x_i) / n — The arithmetic average of a data set.s^2 = sum((x_i - xbar)^2) / (n - 1) — Average squared distance from the sample mean with Bessel correction.Number of siblings: quantitative, discrete, ratio. Satisfaction rating (1-5 stars): qualitative, ordinal. Body temperature: quantitative, continuous, interval. Zip code: qualitative, nominal (even though it uses numbers).
The type of data determines which statistical methods are appropriate. Always identify your data type before choosing an analysis technique.
Go interactive
The interactive lesson for this module is free — track your progress, then keep going with practice questions and calculators.
Keep reading