Introduction to Statistics

ِ‫ن‬ ٰ‫حم‬َّ‫الر‬ ِ‫ہللا‬ ِ‫سم‬ِ‫ب‬‫مم‬ ِ‫ح‬َّ‫الر‬
Presented By
Jahanzaib Shah
JShahHashmi JShahHashmi JShahHashmii Linkedin.com/in/JShahHashmi

Definition, Scope and Limitation

Introduction
 In the modern world of computers and information
technology, the importance of statistics is very well
recognized by all the disciplines.
 Statistics has originated as a science of statehood
and
found applications slowly and steadily in
◦ Agriculture,
◦ Economics,
◦ Commerce,
◦ Biology,
◦ Medicine,
◦ Industry,
◦ Planning, education and so on.
 As on date there is no other human walk of life,
where statistics cannot be applied.

Origin and Growth of Statistics


Origin and Growth of Statistics
 The word ‘ Statistics’ and ‘ Statistical’
are all derived from the
Latin word Status, means a political state.
 Statistics is concerned with scientific
methods for
◦ collecting,
◦ organizing,
◦ summarizing,
◦ presenting and analyzing data
◦ as well as deriving valid
conclusions and making
reasonable decisions on the basis
of this analysis.

Meaning of Statistics
 The word ‘ statistic’ is used to refer to
◦ Numerical facts, such as the number of
people living in particular area.
◦ The study of ways of collecting, analyzing
and interpreting the facts.

Definition by A.L.Bowley
 “Statistics are numerical statement of facts in any
department of enquiry placed in relation to each
other.”
 “Statistics may be rightly called the scheme of
averages.”

Definition by Croxton and Cowden
 “Statistics may be defined as the science of collection,
presentation analysis and interpretation of
numerical data from the logical analysis.”
◦ 1. Collection of Data
◦ 2. Presentation of data
◦ 3. Analysis of data
◦ 4. Interpretation of data

Collection of methods for planning experiments, obtaining
data, and then organizing, summarizing, presenting, analyzing,
interpreting, and drawing conclusions.
 Statistics refers to the body of techniques used for collecting,
organizing, analyzing, and interpreting data. The data may be
quantitative, with values expressed numerically, or they may be
qualitative, with characteristics such as consumer preferences
being tabulated. Statistics is used in business to help make
better decisions by understanding the sources of variation and
by uncovering patterns and relationships in business data
Simple Definition

Statistics are the aggregates of facts
Statistics are affected by a number of factors
Statistics must be reasonably accurate
Statistics must be collected in a systematic
manner
Collected in a systematic manner for a pre-
determined purpose
Lastly, Statistics should be placed in relation to
each other
Characteristics of Statistics

Statistics are the aggregates of facts:-
It means a single figure is not statistics. For example, national income
of a country for a single year is not statistics but the same for two or
more years is statistics.
Statistics are affected by a number of factors:-
For example, sale of a product depends on a number of factors such as
its price, quality, competition, the income of the consumers, and so on.
Statistics must be reasonably accurate:-
Wrong figures, if analyzed, will lead to erroneous conclusions. Hence,
it is necessary that conclusions must be based on accurate figures.
Statistics must be collected in a systematic manner:-
If data are collected in a haphazard manner, they will not be reliable and
will lead to misleading conclusions.

Collected in a systematic manner for a pre-determined
purpose
Statistics should be placed in relation to each other:-
If one collects data unrelated to each other, then such data
will be confusing and will not lead to any logical conclusions.
Data should be comparable over time and over space.

There are two main branches of statistics
Descriptive Statistics
Inferential Statistics

Descriptive Statistics
Descriptive statistics include the techniques that are used to
summarize and describe numerical data for the
Purpose of easier interpretation
EXAMPLE
The monthly sales volume for a product during the past year
can
be described and made meaningful by
Preparing a bar chart or a line graph. The relative sales by
month can be highlighted by calculating an index number
for
each month such that the deviation from 100 for any given
month
indicates the percentage deviation of sales in that month as
compared with average monthly sales during the entire year.

Inferential Statistics
Inferential statistics include those techniques by which
decisions about a statistical population or process are made
based only on a sample having been observed. Because
such decisions are made under conditions of uncertainty, the
use of probability concepts is required
EXAMPLE
In order to estimate the voltage required to cause an
electrical device to fail, a sample of such devices can Be
subjected to increasingly higher voltages until each device
fails. Based on these sample results, the probability of
failure at various voltage levels for the other devices in the
sampled population can be estimated.

How Statistics Work
Statistics starts with a question, not with
data/information
Every time we use statistic to find the solution for a question.
Statistics are what decision makers can use to reduce ambiguity
by qualifying it.
All Statistics are based on data
Data are what we hear, see, smell, taste, touch, etc.
Data requires measuring
Statistics are designed to transform data into information
Make decisions using that information.
Statistics are about and used to measure/assess risk of the
decision

Importance of Statistics
Business and Industry
Health and Medicine
Learning
Research
Social Statistics
Natural Resources

Types of data in Statistics
In statistics, data are classified into two broad categories:
Quantitative data.
Qualitative data.

1:Quantative Data
Quantitative data are those that can be quantified in
definite
units of measurement. These refer to characteristics whose
successive measurements yield quantifiable observations.
Depending on the nature of the variable observed for
measurement.
Quantitative data can be further categorized as
Continuous Data
Discrete Data.

Continuous Data
Continuous data represent the numerical values of a
continuous variable. A continuous variable is the one that can
assume any value between any two points on a line segment,
thus representing an interval of values. The values are quite
precise and close to each other, yet distinguishably different.
All characteristics such as weight, length, height, thickness,
velocity, temperature, tensile strength, etc., represent
continuous variables. Thus, the data recorded on these and
similar other characteristics are called continuous data

Discrete Data
Discrete data are the values assumed by a discrete variable. A
discrete variable is the one whose outcomes are measured in
fixed numbers. Such data are essentially count data. These are
derived from a process of counting, such as the number of items
possessing or not possessing a certain characteristic. The
number of customers visiting a departmental store every day,
the incoming flights at an airport, and the defective items in a
consignment received for sale, are all examples of discrete data.

2:Qualitative Data
Qualitative data refer to qualitative characteristics of a
subject or an object. A characteristic is qualitative in
nature when its
observations are defined and noted in terms of the
presence or absence of a certain attribute in discrete
numbers.

Data Sources in Statistics
Data sources could be seen as of two types, viz., secondary
and primary. The two can be defined as under:
(i) Secondary data: They already exist in some form:
published or unpublished - in an identifiable secondary
source. They are, generally, available from published
source(s), though not necessarily in the form actually
required.
(ii) Primary data: Those data which do not already
exist in
any form, and thus have to be collected for the first time
from the primary source(s). By their very nature, these data
require fresh and first-time collection covering the whole
population or a sample drawn from it.

Functions of Statistics
◦ 1. Condensation
◦ 2. Comparison
◦ 3. Forecasting
◦ 4. Estimation

Scope of Statistics
◦ 1. Statistics and Industry
◦ 2. Statistics and Commerce
◦ 3. Statistics and Agriculture
◦ 4. Statistics and Economics
◦ 5. Statistics and Education
◦ 6. Statistics and Planning
◦ 7. Statistics and Medicine
◦ 8. Statistics and Modern applications

Limitations of Statistics
◦ Statistics is not suitable to the study of
qualitative
phenomenon
◦ Statistics does not study individuals
◦ Statistics laws are not exact
◦ Statistics table may be misused
◦ Statistics is only, one of the methods of
studying a
problem
◦

Introduction to Statistics

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