Classification of Data
In addition to differentiation of data in above four categories, one can Classify The Data into two broad categories:- Qualitative data
- Quantitative data
- â€‹Qualitative data
- â€‹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.
- For example: In qualitative data people with same characteristic are counted to form specific groups or classes e.g.
Attacked, Died, Cured, Vaccinated, Males etc. - The results obtained from qualitative data are expressed as any of these:
- â€‹Ratio
- Proportion
- Percentage
- Rate
- â€‹The statistical methods commonly employed in analysis of qualitative (discrete) data are:
- â€‹Standard error of proportion
- Chi-square test
- 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.
- â€‹Weight
- Height
- Blomod pressure
- Age
Qualitative Data |
Quantitative Data |
Finite, discrete variable |
Infinite, continuous variable |
No Magnitude |
Magnitude â€“ scale |
Rate, ratio, proportion |
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 |
- Methods of Data Presentation
- â€‹Tabular method: for scientific audience e.g in journals etc. Frequency table, association table, correlation table.
- Graphical method: for administrators & lay public: Bar diagram, histogram, frequency polygon.
- Pictorial method: for lay & illiterate public: pictogram.
- â€‹Summarizing Data:
- â€‹Histogram is a pictorial diagram of frequency distribution of grouped data of a continuous variable. (AIâ€™09).
- â€‹â€‹To display a nominal scale data of discrete variable a bar diagram is used.
- â€‹Bar graphs are identical to a histogram except that each rectangle on the graph is clearly separated from the others by a space demonstrating that the data are separate categories. It could be:
- â€‹Simple
- Multiple/Compound
- Component/Proportional
- â€‹Line diagrams are used to show the trend of some event with the passage of time.
- Pie diagram: used for qualitative data, denotes proportion, degree of angle denotes the frequency and area of sector.
- A pictogram is a pictorial depiction of discrete data where symbols are used instead of a bar and the frequency of the event is shown by the number of times the symbols are repeated.
- Scatter diagram is drawn to show the relationship between two variables. Data set needs to be quantitative.â€‹
- â€‹Histogram is a pictorial diagram of frequency distribution of grouped data of a continuous variable. (AIâ€™09).
Extra Edge:
For Calculating exponential growth:
P (Final Value) = c (Initial value) [ 1 + r (Fractional increase) ] ^{n}
e.g.: one bacteria divides every 30 min for 4 hrs. If the growth follows exponential pattern, bacterial population after 4 hours:
4 hrs = 180 min
30 min = (180 /30) = 6 times
n = 6
c = 1, initial population
r = 1, fractional increase
(1 + r)^{n} = (1+1)6 = 2^{6}
P = 2^{6} = 64