This document provides an overview of biostatistics and different types of variables and data. It defines biostatistics as the application of statistical methods to biological and health data. It discusses qualitative and quantitative variables and different types of each. Qualitative variables are categorical and include binary, nominal, and ordinal variables. Quantitative variables are numerical and include continuous and discrete data. The document also outlines different types of data: nominal data involves names or labels without order; ordinal data adds order; interval data involves equal distances on a scale; and ratio data has a true zero point and ratios can be calculated.

1. BIOSTATISTICS
MODULE-10
Dr Qurat-Ul-Ain
Assistant Professor / HoD
Community Dentistry Department
HBS Medical & Dental College

3. BIO - STATISTICS
Two words bio and statistics
1. Bio :
that relating to biological
problems or living organisms
2. Statistics :
data gathering

4. BIOSTATISTICS
• DEFINITION
Statistical processes and methods applied to the
collection, analysis, and interpretation of
biological data and especially data relating to
human biology, health, and medicine

5. VARIABLES
• A variable is a factor that can
take different values for
individuals in a study
• Variable is something that we
can measure as well as
manipulate
• Experimental or non-
experimental studies
• Dependent and independent
variable

8. VARIABLE
Examples
• Age
• Weight
• Business Income
• Expenses,
• Country Of Birth
• Capital Expenditure
• Class Grades

9. TYPES OF VARIABLE
1. Variable may Qualitative (Categorical – Describe attribute)
• Binary
• Nominal
• Ordinal
2. Variables may Quantitative (Numerical values)
• Continuous Data
• Discrete Data

10. QUALITATIVE = CATEGORICAL VARIABLE
1. Binary:
Allocation of observations to one of only two possible
categories.
Example, Gender m/f , yes/no, True/False

11. QUALITATIVE = CATEGORICAL VARIABLE
2. Nominal:
• Allocation of observations into
more than two categories.
• The data cant be ranked or
grouped in any order at all
• Example, Brown Black Red
Silver Yellow

12. QUALITATIVE = CATEGORICAL VARIABLE
3. Ordinal:
Allocation of observations into more
than two categories that can be
ordered.
Example
Unhappy - Ok Happy - Very Happy
Anxious - Not anxious - Very anxious –
Extremely
anxious

14. QUANTITATIVE = NUMERICAL VARIABLES
1. Continuous Data: A set of data is said to be continuous
if the values are measurements that can assume any
value within a specified range.
Example: Temperature ,Height, Weight

15. QUALITATIVE = CATEGORICAL VARIABLE
2. Discrete Data: A set of data is said to be discrete if the
values are distinct and separate. That is, they can be
counted (1,2,3, ...).
Example : Number of new TB cases in a month /
Number of patients in a clinic

16. DATA
• Data is a set of values of qualitative or quantitative
variables.
• Facts or figures to be processed; evidence, records,
statistics, etc. from which conclusions can be inferred

19. 1- QUANTITIVE OR (NUMERICAL DATA).
Data which can be measured with a scale or
which gives numeric values
Example;
1. Age
2. weight & Hight
3. Temperature
4. Blood pressure
5. How many pages you can read of your
favorite book before you fall asleep

20. 2-QUALITATIVE OR CATEGORICAL DATA
Data which can be counted or which has
different categories
Example;
1. Gender
2. Blood Group
3. Marital Status
4. Hometown
5. Types of Movies they Like

21. CLASSIFICATION OF DATA
• Data can classified in number of ways, one is as
described above Qualitative & Quantitative
• Others types are;
1. Nominal Data
2. Ordinal Data
3. Interval
4. Ratio

22. NOMINAL DATA
• This type of data is in the form of names, labels or
categories.
• It cannot be ranked or grouped in any order.
• Nominal is the lowest level. Only names are
meaningful here.
Example; Gender , Race, Type of teeth ect

23. ORDINAL DATA
• Ordinal adds an order to the name
Example
• Large, Medium, Small
• Good, Bad, Malnourished
• Normal , Overweight, Obese,
• Decayed , Missing , Filled

24. INTERVAL DATA
• Interval data is a type of data which is measured
along a scale, in which each point is placed at an
equal distance (interval) from one another.
• Examples;
1. Temperature
2. Time
3. IQ

25. INTERVAL DATA
1. Temperature
An example of interval data is the
data collected on a thermometer—
its gradation or markings are
equidistant.

26. INTERVAL DATA
2. Time
• Time passes as a good example of interval
data if measured during the day or using a
12-hour clock. The numbers on a wall clock
are on an interval scale since they are
equidistant and measurable.
• For example, the difference between 1
o’clock and 2 o’clock is the same as that
between 2 o’clock and 3 o’clock.

27. INTERVAL DATA
3. IQ Test
• According to psychological
studies, one can not have zero
IQ. Also, IQ is determined using
a fixed measurement scale.
Therefore, IQ is an example of
interval data.

28. RATIO DATA
Similar to interval but ratio has a true
ZERO or starting point
Example;
Hight, Weight, Length, distance,
traveled
Each point value can be expressed as
meaningful ratio to another e.g twice
the weight

29. EXAMPLES
What is your weight in kgs?
• Less than 50 kgs
• 51-60 kgs
• 61-70 kgs
• 71-80 kgs
• 81-90 kgs
• Above 90 Kgs
What is your height in feet
and inches?
• Less than 5 feet.
• 5 feet 1 inch – 5 feet 5
inches
• 5 feet 6 inches- 6 feet
• More than 6 feet
What is the number of
burgers you can eat daily?
• 1-2
• 2-3
• 3-4
• 4-5
• 5-6
• More than 6

31. Questions