Bio statistic (lecture 01)

Biostatistics
Muhammad Alfahad
Farwa Butt
alfahadfarwa786@gmail.com

Statistics has been defined differently by different authors from time to time. Generally it is
considered to be the subject that deals with percentage, charts and tables.
 The word statistics comes from the Latin word status, meaning a political state originally meant
information useful to the state e.g. information about the size of populations and armed forces.
 The word statistics is defined as a discipline that includes procedure and techniques used to
i) Collect
ii) Process
iii) Analyze numerical data to make inference and to reach decision in the face of uncertainty.
Introduction to Statistics

Different Meanings of Statistics
1. Numerical Facts
e.g. Statistics of prices, Statistics of road incidents, Statistics of crimes
Statistics of births, Statistics of deaths, Statistics of institutions etc.
2. Statistics as a subject
Statistics is the science of making decisions and drawing conclusions from data in situations of uncertainty.
It includes collection, organize and analysis of numerical data.
3. Statistic.
A numerical quantity calculated from a sample

Biostatistics
 When the principles of statistics are applied to a study of living system, the study is called Biostatistics.
 When the data analyzed are derived from the biological sciences and medicine, we use the term
biostatistics to distinguish this particular application of statistical tools and concepts
 In Pharmacology
a. To find action of drug
– a drug is given to animals or humans to see whether the changes produced are due to the drug or
by chance.
Different application of Biostatistics

a. To compare action of two different drugs
b. To find relative potency of a new drug with respect to a standard drug.
 In Medicine
a. To compare efficiency of particular treatment.
– for this, the percentage cured or died in the experiment and control groups, is compared and difference due to
chance or otherwise is found by applying statistical techniques.
b. To find association between two attributes e.g. cancer and smoking

Population and Sample
Population
 A population or statistical population is a collection of all observation whether finite or in finite relevant
to some character of interest.
 The size of population is donated by “N”. Numerical quantities describing a population are called
parameters.
Sample
 A sample is a part of population. Generally it consist of some observation and the number of observation
include in a sample are denoted by “n”.
 A numerical quantity computed from a sample is called a statistic.
Parameter: It is a quantity computed from a population if the entire population is available. Parameters are
fixed or constant quantities and not usually known.
Statistic: It is a quantity computed from sample. Statistics are variables because they vary from sample to
sample alfahadfarwa786@gmail.com

Example:
It was observed that out of 500 rabbits caught, 300 were females and 200 are male. Is there evidence
that more rabbits in this country are females?
Solution:
Population:
Rabbits all over the country.
Sample:
500 rabbits caught.
Parameter:
Ratio, Proportion, Percentage etc. of male and female rabbits all over the country rabbits
Statistics:
The ratio of male to female rabbits ‗ 200 ‗ 2
300 3
The ratio of female to male rabbits ‗ 300 ‗ 3
200 2

Branches of Biostatistics
Biostatistics as a subject is divided into two parts
1) Descriptive Biostatistics
2) Inferential Biostatistics
Descriptive Biostatistics
 The branch of statistics which deals with concept and methods concerned with summarization and
description of the important aspect of numerical data.
This area of study consist of the
i) condensation of the data
ii) their graphical representation
iii) computation of few numerical quantities that provide the center as well as the spreadness of the
observation

Branches of Biostatistics
Inferential Biostatistics
 This branch of statistics deals with procedure for making inferences about the characteristics that describe
the large group of the data called the population from the knowledge derived from only a part of the data
known as sample.
This area includes the
i) estimation of population parameters
ii) testing of statistics hypotheses.

Observation, Variable and Constants
 Numerical recording of information whether it is physical measurement (weight, height) or classification
such as heads or tails are called observation.
 A characteristics that varies with an individual is called a variable. For example age is variable as it
varies from person to person.
 A characteristics that does not varies with individuals is called a constant. For example if price of meat is
the same in all over the market, then it will be called a constant.

Types of Variable
Variable may be classified into quantitative and qualitative according to the form of the characteristic of
interest.
Quantitative Variable
 A variable is called quantitative variable when a characteristic can be expressed numerically such as
weight, number of children’s etc.
Qualitative Variable
 If a characteristic is expressed non-numerically such as education, gender eye color etc. the variable
referred to as qualitative variable.

Discrete and Continuous Variable
A quantitative variable may be classified as a discrete or continuous.
Discrete Variable
A discrete variable is the one that takes only a discrete set of integer or whole numbers. A discrete variable
represent a count data such as the number of persons in family, the number of death in a accident.
Continuous Variable
A quantitative variable is called continuous if it take any fractional value within give interval without any
gap e.g. height, weight of a person.
 A variable whether it is countable or measurable is denoted by some symbol such as X or Y and Xi or Yi
represents the ith and jth value of the variable.

The measurement of scale means assigning of numbers to the observation or objects in a process of
measuring. The four scale of measurement are
i) Nominal scale
ii) Ordinal scale
iii) Interval scale
iv) Ratio scale
Nominal Scale
 The classification of observations into qualitative categories are said to constitute a nominal scale. For
example the students are classified as a “male” or “female”, “pass” or “fail”.
 The numbers 1 and 2 may also used to identify these categories. These numbers are only used to identify
the categories of given scale and there is no numerical significance of these numbers.
Measurement of Scale

Ordinal Scale
It includes the characteristic of nominal scale and in addition has the property of ordering or ranking of
measurements.
For example
•Attitude scale; Strongly agree, agree, disagree
•performance of students; Excellent, good, poor etc.
• Social scale : Upper, middle, lower
• Performance of players: Excellent, good, fair, poor
The numbers 1, 2, 3 are also used to indicate ranks.

Interval Scale
A measurement scale possessing a constant interval size but not true zero point is called interval scale e.g.
temperature where 0 ˚ C does not mean no temperature.
 In addition they have meaningful intervals between items. For example on the Celsius scale the difference
between 100 ˚ C and 90 ˚ C is the same as the difference between 50 ˚ C and 40 ˚ C.
Ratio Scale
It is a special kind of interval scale where the scale of measurement has a true zero point. The ratio scale is
used to measure weight, length, distance , money etc.
 The key to differentiating interval and ratio scale is that the zero point is meaning for ratio scale.
 It is correct to say that a pulse rate of 120 beats/min is twice as fast as pulse rate of 60 beats / min.
 Variable measured on the ratio scale cannot assume negative values.

Table: Summary of Measurement of Scale

Bio statistic (lecture 01)

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