Types of Data and Their Presentation

Introduction

• The first step in any analysis — before any calculation, summary, or plot — is to decide the type of each variable, because the data type dictates which summary statistic is legitimate and which display is appropriate.
• Variable vs observation — a variable is any characteristic that varies between members of a sample (age, sex, blood concentration, diagnostic category); the recorded value for one individual is an observation.
• The data type fixes three downstream decisions at once: (i) the measure of central tendency (mean vs median vs mode), (ii) the measure of variation (SD vs IQR vs range), and (iii) the tabular/graphical method (bar vs histogram vs pie vs scatter).
• PG framing — the data type is a property of the measurement scale, not of the phenomenon — blood pressure in mmHg is continuous, but the same construct dichotomised at a threshold ("hypertensive yes/no") becomes binary; reducing a continuous variable to categories discards information and is justified only when clinically meaningful.