Statistics basics

M A H U Y A D E B
Statistics Basics

Statistics
Decision making is a critical part of our day to day life .
Examples
Purchasing a new television
Introducing a new product in the product
Hence data collection is the backbone of any decision
making process.

Organisations may find themselves data rich but poor
in drawing information from it.
Therefore it is important to develop the ability to
extract meaningful information from raw data to make
better decisions.
Statistics play an important role in this aspect.

 The systematic treatment of quantitative expression is
known as “statistics”.
 Statistics can be defined in two ways :
(a) In plural sense
(b) in singular sense
Figures are innocent and they do not speak anything . But
when they refer to some place, person, time etc. they are
called statistics. For eg statistics of scores in a cricket
match , statistics of price , statistics of agricultural
production , statistics of export and import etc.

Definition of Statistics
 According to Horace Secrist , “ By statistics we mean
aggregate of facts affected to a marked extent by
multiplicity of causes numerically expressed,
enumerated, or estimated according to reasonable
standards of accuracy , collected in a systematic manner
for a predetermined purpose and placed in relation to
each other.

 Statistics in its second , singular sense , refers to the
methods adopted for scientific , emperical studies.
 Whenever a large amount of numerical data are
collected , there arises a need to organise, present ,
analyse , and interpret them .Statistical method deal
with these stages.

 According to Croxton and Cowden ,”Statistics may
be defined as a science of collection , presentation ,
analysis and interpretation of numerical data”.
 Collection
 Organisation
 Presentation
 Analysis
 Interpretation

Statistics is broadly divided into two main categories
 Descriptive Statistics
 Inferential
Descriptive Statistics is mainly concerned with
Collecting
Organising
Summarising
Presenting the data
Inferential Statistics is concerned with
Making Inference
Hypotheseis Testing
Determinning relationships
Making Prediction

Scope and Application of Statistics
 Statistical methods are applied to specific problems
in various fields such as Biology, Medicine,
Agriculture, Commerce,Business, Economics,
Industry,Insurance, Sociology and Psychology.

 In the field of medicine , statistical tools like t-tests are
used to test the efficiency of the new drug or medicine .
 In the field of economics , statistical tools such as index
numbers, estimation theory and time series analysis are
used in solving economic problems related to wages ,
price ,production and distribution of income .
 In the field of agriculture , an important concept of
statistics such as analysis of variance (ANOVA) is usedin
the experiments related to agricultre , to test the
significance between two sample means .

 In biology, medicine and agriculture, statistical
methods are applied in the
 Study of growth of plamts
 Movement of fish population in the ocean
 Migration pattern of birds
 Analysing the effect of newly invented medicines
 Theories of heredity

 Estimation of yield of crops
 Study the effect of fertilizer on yield
 Birth rate
 Death rate
 Population growth
 Growth of bacteria

 Insurance companies decide on the insurance premiums
based on the age composition of the population and the
mortality rate. Actuarial science is used for the
calculation of insurance premiums and dividends.
 A governments admenistrative system is fully dependent
on production statistics, income statistics, labour
statistics, economic indices of price of cost, price
 In manufacturing industries, statistical quality control
techniques help in incresing and controlling the quality
of product at minimum cost .

Function of statistic
 Statistics simplifies complex data
 The table displays the rating (scale of 1 to 10) for a
regional movie given by 50 customers
1, 5, 7, 6, 8, 7, 5, 3, 4, 7, 1, 2, 5, 8, 7, 4,
7, 4, 2, 4, 9, 8, 7, 2, 5, 4, 5, 7, 9, 8, 7, 8,
9, 6, 7, 2, 3, 2, 8, 7, 6, 3, 5, 7, 6, 3, 9, 5,
4, 8,

 Using statistical concept such as calculating frequency and frequency
distribution and draw conclusions and the frequency table is prepared.
RATING FREQUENCY FREQUENCY
DISTRIBUTIO
N
1 2 2/50=0.04
2 5 5/50=0.10
3 4 4/50=0.08
4 6 6/50=0.12
5 7 7/50=0.14
6 4 4/50=0.08
7 11 11/50=0.22
8 7 7/50=0.14
9 4 4/50=0.08
10 0 0/50=0

 Statistic make comparison easier
 Statistic bring out trends and tendencies in the data
 It brings out the relations between variables
 Decision making power becomes easier

Limitations
 Statistics does not deal with qualitative data
 Statistics does not deal with individual fact
 Statistical inferences are not exact
 Statistics can be misused and misinterpreted
 Common man cannot handle statistics properly

Basic terms used in statistics
 Units- in a statistical survey the objects on which the
characteristics are measured are called units.
 Population or universe – the totality of all units or
individuals in a survey in called population. If the
number of objects in a population in finite then it Is
called finite population otherwise it is known as
infinite population.
the data that describes the characteristics of the
population is known as parameter

 Sample – it is part or subset of the population. The data that
describes the characteristic of the sample is known as statistics.
 Quantitative characteristics – a characteristic which is numerically
measurable.
 Qualitative characteristics – a characteristic which is not
numerically measurable.
 Variable – the quantitative characteristic that varies from unit to
unit.
A variable that assumes only some specified in a given range is
known as discrete variable. A variable that assumes all the values in
the range is known as continous variable. Example : the number of
children per family and number of petals in a flower are examples of
dicrete variables. The height and weight of persons are examples of
continous variables

 Attribute – the qualitative characteristics that varies
from unit to unit is called an attribute.
 Question : classify the following as attribute or
variable
1) eye color of human being
2) number of pages in a book of various
subjects

 Question: classify the following as finite or infinite
population
1) production of a product in a factory for a day
2) number of points in a page
3) the weight of newborn babies in a state during the
first week of january 2019

 Question: classify the following as discrete or
continous
1) number of shares sold each day in a stock market
2) temperatures recorded every half hour at a
regional meteorological centre

Sources of Data
 Internal
 External (Primary and secondary)

Collection of data
 Primary data – the data collected for the first time
keeping in view the objectives of the survey are
known as primary data .Collection of primary data
can be done by any one of the following methods.
 Direct personal observation
 Indirect oral interview
 Information through correspondents
 Mailed Questionnaire
 Information through schedule filled by investigators.

Direct Personal Observation
 It is suitable in cases where
 The scope of investigation is narrow
 Investigation is confidential and requires personal
attention of the investigator
 Accuracy of data is important. However personal
bias can give wrong result and the method is lengthy
and complex.

Merits Demerits
1. We get the original data which is
more accurate and reliable
1. The method consumes more cost.
2. Satisfactory information can be
extracted by the investigator through
indirect questions.
2. The method consumes more time
3. Data is homogenous and comparable 3. This method cannot be used when
the scope of investigation is wide
4. Additional information can be
gathered
4. Most of data collected through this
method is maintained confidential .
Hence there is a chance of leakage of
data.
5. Misinterpretation of questions can be
avoided.

Indirect Oral Interview
 Is used when the area to be covered is large
 Data is collected from a third party or witness or
head of institution .
 Generally used by police department in cases related
to enquiries on causes of fires, thefts, or murders.
As the information is obtained from the third party
and not by the person directly concerned, there exists a
possibility of not getting true information. Different
attitudes of different correspondents and agents may
increase errors.

Merits Demerits
1.Economical in terms of the time, cost
and man power
1. The degree of accuracy of information
is less.
2. Confidential information can be
collected
3. Information is likely to be unbiased
and reliable.

Collecting information through agencies
 Methods of collecting information through local or
correspondents are generally adopted by newspaper
and television channels. Local agents are appointed
in different parts of the area under investigation.
 It is used where the area to be covered is very large
and periodic information is required.
 However one disadvantage of this method is that the
information is likely to be affected by the bias of the
correspondents or agencies.

Mailed Questionnaires
 A list of questions relating to enquiry, is called schedule or
questionnaire. The questionnaires are filled with questions
pertaining to the investigation . They are sent to the
respondents with a covering letter soliciting cooperation from
the respondents.
 Good questionnaire construction is an important contributing
factor to the success of a survey.
 Generally adopted by research workers and other official and
non-official agencies.
 Used to cover large areas of investigation .
 More economical and free from investigator’s bias.
 However it may result in non response situations and the
respondent may provide wrong information due to wrong
interpretation of questions

Information through schedule
 Information can be collected through schedules filled
by investigators through personal contact . In order
to get reliable information , the investigator should
be well trained , tactful, unbiased and hard working .
 It is useful for an extensive area of investigation
through investigator’s personal contact. The problem
of non-response is minimised.

Secondary data
 Any information that is used for the current
investigation but is obtained from some data , which
has been collected and used by some other agency or
person in a separate investigation or survey is known
as secondary data.
 They are available in published or unpublished form.

 In published form, secondary data is available in
research papers, news papers,magazines ,
government publication , international publication
,and websites. Secondary data is collected for
different purposes. Therefore , care should be
exercised while making use of it .
 The accuracy, reliability , objectives and scope of
secondary data should be examined thoroughly
before use. Secondary data may be collected either
by census or sampling methods.

Sources of published data
 Reports and official publications of international and
national organisations as well as central and state
governments.
 Publications of several local bodies such as municipal
corporations and district boards
 Financial and economic journals.
 Annual reports of various companies.
 Publications brought out by research agencies and
research bodies.
 Journals published at regular intervals like yearly ,
monthly, weekly etc.

 Unpublished data such as records maintained by various
government and private offices, studies made by research
institutions and scholars can be used where necessary .
 Some of the measures that need to be considered while
using secondary data.
 The collection and processing of the data.
 Accuracy of the data.
 The degree of the summarization of the data
 The degree of comparable the data is with other
tabulations
 How to interpret the data , especially when figures,
collected for one purpose is used for another.

Merits and Demerits of Secondary Data
Merits Demerits
1. Secondary data is cheaper to obtain. Many
government publications are relatively cheap
and libraries stock quantities of secondary
data produced by the government , by
companies and other organisations.
1. It is difficult to judge whether the
secondary data is sufficiently accurate.
2. Large quantities of secondary data can be
accessed through the internet.
2. It might be difficult to fit secondary data
to the needs of the investigator.
3. It is valuable to the government , business
and research areas. In Govt. ,it helps in
making decisions and in planning future
policies. To the research orgnisation , it helps
by providing social , economical and
industrial information
3. Secondary data might not be available for
certain investigations. In such situations ,
primary data has to be collected.

Difference between primary and secondary Data
Primary Data Secondary Data
1. Data is original and thus more
accurate and reliable
1. Data is not reliable
2. Gathering data is expensive 2. Gathering data is cheap
3. Data is not easily accessible. 3. Data is easily accessible through
internet or other sources.
4. Most of the data is homogenous 4. Data is not homogenous
5. Collection of data requires more time 5. Collection of data requires less time
6. Extra precautionary measures need
not be taken
6. Data needs extra care

 State whether the following data are primary or
secondary
i) An official of the Census Board of India is preparing a
report on the census of population based on the survey
data collected by the Census Board.
ii) An HR representative of a software company is deciding
on the time taken to perform a particular job on a project
on the basis of random observations collected by him .
iii) A neurologist is examining the relationship between
cigarette smoking and brain tumor based on the data
published in a famous neurology journal.

 State whether the following statements are “True” or
“False”.
 Census conducted by Government of India is an
example of primary data.
 TV News Bulletins gather information on any event
through their agents.
 Schedules make respondents record their answers.
 A covering letter to the questionnaire brings
confidence in respondents.
 Questions in questionnaire should be lengthy.

Statistics basics

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