Mean and SD can be worked out only if the data is on:
|A||Interval / Ratio scale|
One can CLASSIFY THE DATA into two broad categories:
i. Qualitative data
ii. Quantitative data
A. Qualitative data
Also known as discrete data. It is composed of only certain values and none in between like 3 or 4 but not anything in between. It is classified only by counting the variables (e.g. individuals) having the same characteristics e.g.
Qualitative data are either Nominal or Ordinal
In qualitative data people with same characteristic are counted to form specific groups or classes e.g.
v. Males etc.
vi. Pharmacology: to find the action of a drug
vii. Clinical practice: to test or compare efficacy of a drug/vaccine/treatment
viii. Demography: to find births/deaths/stillbirths etc.
ix. No of patients in the ward
The results obtained from qualitative data are expressed as any of these:
The statistical methods commonly employed in analysis of qualitative (discrete) data are:
a. Standard error of proportion
b. Chi-square test
B. Quantitative data
It is also known as continuous data. Discrete (qualitative) data can take only certain values, and none in between if the data can take any value; it is called continuous (quantitative) data. Most biomedical variables are continuous e.g.
- Blood pressure
Quantitative data can be either an Interval or Ratio variable and are summarized as Mean, SD or Correlation Coefficient.
The statistical methods commonly employed in analysis of quantitative (continuous) data are:
i. T test
ii. Z test
iii. F test
Finite, discrete variable
Infinite, continuous variable
Magnitude – scale
Summarized as Rate, ratio, proportion
Summarized as Mean, SD, correlation coefficient
Bar, pie, pictogram, spot map
Histogram; Frequency polygon; Line diagram, Scatter diagram
Answer to question is in Yes / No
Answer to question is an quantitative value with unit