Dr Zia-Ul-Ain Sabiha
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At the end of this session the students will be
able to
Define Statistics
Differentiate between Descriptive Statistics
and Inferential Statistics
Define Biostatistics
Discuss the Uses of Biostatistics
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Define
Data
Sample and Population
Variables
Measurement variables
Types of Data
Exercises to summarize the lecture.
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Statistics is science of conducting studies to
collect ,organize, summarize, analyze, and
draw conclusions from the data.
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A subject that deals with the collection ,
compilation , presentation , analysis and
presentation of data.
Drawing inferences about a body of data
when only a part of the data is observed.
Scientific study of numerical data based on
natural phenomenon
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Descriptive Statistics
Consists of the collection , organization ,
summarization, and presentation of data.
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Inferential statistics
consists of generalizing from samples to
populations ,performing estimations and
hypothesis tests, determining relationships
among variables and making predictions.
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It uses probability i,e., the chance of event
occuring
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The origin of descriptive Statistics can be
traced to data collection methods used in
censuses taken by the Babylonians and
Egyptians between 4500 and 3000 B.C.
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In addition the Roman Emperor Augustus (27
B.C-A.D. 17) conducted surveys on births and
deaths of the citizens of the empire, as well
as the number of livestock each owned and
the crops each citizen harvested yearly.
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Inferential Statistics originated in the 1600s,
when John Graunt published his book on
population growth , Natural and Political
Observations Made upon the Bills of Mortality.
About the same time ,another
mathematician/astronomer , Edmund Hally,
published the first complete mortality
tables.( insurance companies use mortality
tables to determine life insurance rates).
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Application of Statistical methods to the
solution of biological problems
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In Epidemiology
In demography
Morbidity and mortality rates and ratios.
Collection and registration of vital events.(Births
,Deaths , Marriages and divorces)
 Sampling for different statistical procedures.
 To know the frequency of different diseases and
biological problems.
 For interpretation of data.
 To know about association and causation of
diseases.
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Record of observations
Facts and figures
Any piece of information
Information
When data is processed and made
meaningful
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Data are numbers which can be measured or
can be obtained by counting. Biostatistics is
concerned with the interpretation of the data
and the communication of information about
the data.
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Data are obtained from
 Analysis of records
 Surveys
 Counting
 Experiments
 Reports
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A characteristics ,object and property that
assumes different numerical value for each
possible outcome/individual/element of the
population or sample is called a variable.
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The actual property measured on the
individual selected for sample.
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E.g. Height ,weight
,temprature,age,smoking,
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A random variable is one that cannot be predicted in advance because it
arises by chance. Observations or measurements are used to obtain the
value of a random variable.
Random variables may be discrete or continuous.
Discrete random variable
A discrete random variable has gaps or interruptions in the values that it
can have. The values may be whole numbers or have spaces between
them.
Continuous random variable
A continuous random variable does not have gaps in the values it can
assume. Its properties are like the real numbers.
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Independent and dependent
Independent variables are presumed causes
and dependent variables are presumed
effects.
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The whole set of things about which we want
to know.
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In biostatistics population can be human
beings , ECG machines , Paracetamol tablets.
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A population is the collection or set of all of
the values that a variable may have. A
sample is a part of a population.
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A part or subset of
population for actual
study. OR
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A collection of
individual observations
selected by a specific
procedure from a
population.
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Measurement variable
 Continuous variables
 Discontinuous variables or discrete variable
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Ranked variables
Categorical variable
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Continuous variables
 Which at least theoretically can assume an infinite
number of values between any two points . e. g
length ,period of time ,height , weight , age ,
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Discrete, Discontinuous variables
 That has only certain fixed numerical values with
no intermediate values possible in between. e.g.
number of offsprings , no. of teeth, no. of glands.
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Which cannot be measured but ranked or
ordered .e.g. rank order of pupa emergence
or seed germination.
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The characteristics that are qualitative in
character and hence cannot be expressed
numerically( or quantitatively) are called
descriptive characteristics or attributes.
 The sex of a newly born baby.
 Eye color of a girl.
 The language of a Arabian visitor.
 The style of a speaker
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Data consists of variables.
There are four scales of measurement
 Nominal(category)
 Ordinal(category)
 Interval(quantity ,continuous )
 Ratio(quantity , continuous)
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Scale
Characteristic question
Example
Nominal
Is A different than B?
Marital status
Eye color
Gender
Religious affiliations
Race
ordinal
Is A bigger than B?
Stage of disease
Severity of pain
Level of satisfaction
Interval
By how many units do A and B
differs?
Temperature
SAT score
Ratio
How many times bigger than B is A? Distance
Length
Time until death
Weight
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Classifies persons or things based on the
characteristic being assessed
No information is given on quantity or
amount
A variable without an intrinsic order.
Examples
Male or female
Nationality (American , Mexican , Pakistani)
Favorite pet( dog , cat, fish, snake)
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Classifies persons or things based on the
characteristic being assessed
Can be placed in meaningful order,
Indicates “more than” or “less than”
Does not indicate how much more or how
much less than
Example: Rating a student’s performance as
‘good’, ‘fair’, ‘poor’
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Classifies persons or things based on the
characteristic being assessed
Indicates “more than” or “less than ” and the
magnitude of the observation
There is no true zero or meaningful zero.
Examples
Temperature
Year of birth
Date of diagnosis
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Classifies persons or things based on the
characteristic being assessed
 Indicates “more than” or “less than” and the
magnitude of the observation
 Zero point is indicated
 True ratios exist when the same variable is
measured on the different members f the
population.
 Examples:
 Height
 Weight
 Age
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Date of diagnosis
Town of residence
Age (years)
Sex
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Date of diagnosis: Interval
Town of residence: Nominal
Age (years): Ratio
Sex : Nominal
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Name the scale of measurement for each
variable below:
Year of birth:
Marital status of a women:
Identification number of study participants:
Class rank:
Length of infants at ANC clinic:
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Year of birth: Interval
Marital status of a women: Nominal
Identification number : Nominal
Class rank: Ordinal
Length/Height of infants at ANC clinic: Ratio
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Identify whether the following data is discrete
or continuous
Distance from primary health center to
reference lab:
Number of times a child under 5 has experienced
fever in the last month:
Number of fatal accidents on a road over the
past year:
Weight gained or lost by a 9 month old in the
past 3 months:
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Distance from primary health center to
reference lab: Continuous
Number of times a child under 5 has
experienced fever in the last month: Discrete
Number of fatal accidents on a road over the
past year: Discrete
Weight gained or lost by a 9 month old in the
past 3 months: Continuous
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