This document discusses different types of data including qualitative and quantitative data. Qualitative data can be nominal, ordinal, or categorical. Quantitative data can be continuous like height or weight, or discrete like number of children. Continuous data can be measured on a scale and may include decimals, while discrete data only takes whole number values. Variables are characteristics that are measured or observed, and can be either qualitative or quantitative. The type of statistical analysis used depends on whether the data is qualitative or quantitative.

1. By Dr Aijaz Ahmed Sohag
Prep by: Abdul Wasay Baloch
Amna Inayat Medical College
Data

2. Data
collecting
classifying
Summarizing analyzing
Interpreting numerical
data
Variables
Qualitative
Quantitative
Discrete
Continuous
Ordinal
Nominal

3. Continuous:
Blood pressure , height
weight
Discontinuous :
No of children
No of attacks of asthma per
week
Qualitative

4. Categorical
Ordinal
 Ordered categories
 Grade of breast cancer
 Better, same or worst
 Disagree, neutral, agree
Nominal
 Sex
 Alive or dead
 Blood group O, A, AB

5. Qualitative
 Countable facts
 Discrete
 Only frequency changes
 Can be expressed in rate
ratio
 Use Bar, Pie, Picto and spot
maps
 Test used – chi square,
Standard error of
proportion
Quantitative
 Measureable facts
 Continuous
 Both frequency and
variable changes
 Expressed as mean, median
and mode
 Rest all diagrams, such as
histo scatter and other
 Test used – ANOVA,Z test
and T Tesst

6. Data Defines as
 ‘’ collection of observation in scientific way’’

7. Types
 It has two types
 Qualitative
 Quantitative

8. Qualitative Data
 Qualitative data is categorized as data expressed not in terms
of number, e.g. favorite color, height is tall
 TYPES:
 Normal : when there is not a natural ordringof the categories,
e.g. gender, race, religion
 Ordinal or Ordered/ Ranked Data: when the categories: when
the categories may be ordered, these are called ordinal variable
e.g. small, medium, large
 NOTE that the distance between these categories is not
measured
 Used for both qualitative and quantitative

9. Quantitative
Data

10. Quantitative Data
 It is a numerical measurement expressed in terms of
numbers
 However, not all the numbers are continuous and
measureable
 E.g. favourite color = 450 nm, height = 1.8m

11. Discrete
 When you just count the numbers e.g 10 pencils
 Can not be expressed in decimal
 Thought countable, take only whole number values e.g. No of
children

12. Continuous
 This is measured on some scale
 It has no ends
 E.g. counting the pulse rate of class
 Measuring BP
 Can be measured in decimal
 May be measure as fractional values e.g. 17.4C, 162.5 cm etc)

13. Variables
 Characteristic :
 Any characteristic whose value is different from one individual
to another e.g. height of school boy
 A variable is any characteristic which is measured or observed
 It is denoted by X
 Variables are characteristics associated with the subjects of
study e.g. height weight, gender
 Variables so called because they tend to vary between subjects
 Broadly variables are grouped into quantitative and qualitative
variables

14. Quantitative Variables
 Data can be further classified beig qualitative or quantitative
 The STATISTICAL ANALYSIS that is appropriate depends
on whether the data for variable is qualitative or quantitative
 In general, there are more alternatives for statistical analysis
when the data are Quantitative

15. Quantitative Data
 Indicate either how many or how much
 Always numeric
 Ordinary arithmetic operation (e.g. +,- etc) are meaningful
only with QULITATIVE DATA