STATISTICS INTRODUCTION A.pptx

INTRODUCTIO
N TO
STATISTICS
UNIT 1
DR. MANISHA SETH

DEFINITIONS
According to Prof. Horace Secrist:
 "Statistics is the aggregate of facts affected to a marked extent by the multiplicity of causes, numerically
expressed, enumerated or estimated according to reasonable standards of accuracy, collected in a
systematic manner for a pre-determined purpose and placed in relation to each other."
 “The subject statistics is concerned with the collection, presentation, description and analysis of data
which are measurable in numerical forms” P.H Karmel
DR. MANISHA SETH

Conclusion : Statistics is a science and an art which deals with collection,
classification, tabulation, presentation, establishment of relationship,
interpretation and forecasting of data in connection with social, economic,
natural and other problems so that predetermined aims may be achieved”
DR. MANISHA SETH

CHIEF CHARACTERISTICS OF STATISTICS
 Statistics are aggregate of facts
 Statistics must be numerically expressed
 Statistics should be collected for a pre-determined purpose
 Statistics should be collected in a systematic manner
 Statistics should be capable of being placed in relation to each other
 Statistics are affected to a great extent by a multiplicity of causes
 Statistics are enumerated or estimated according to reasonable standards of accuracy
 A reasonable standard of accuracy should be maintained in the collection of statistics
DR. MANISHA SETH

1. STATISTICS ARE AGGREGATE OF FACTS
 A single numerical figure is not statistics. For example, the height of an individual, the price of a certain
commodity does not form statistics as are unrelated and incomparable.
 But the aggregate of such figures of births, imports, exports, etc. constitute statistics as these figures
can study in relation to time, place, and frequency of occurred.
DR. MANISHA SETH

STATISTICS MUST BE NUMERICALLY EXPRESSED
 Qualitatively expressed statements such as “india is a developing country", "The cement production
in Indiais increasing", etc. do not constitute statistics.
 But the quantitative statement In 1990, the production of wheat was 20 thousand metric tonnes
compared to 15 thousand metric tonnes in 1985" constitutes statistics.
DR. MANISHA SETH

STATISTICS SHOULD BE COLLECTED FOR A PRE-
DETERMINED PURPOSE
 The objective or the purpose of the inquiry should be clearly stated before collecting the data. The data
collected without any pre-determined purpose objective may not be useful for the inquiry. So it is of at most
important define in clear and concrete terms the objective or the purpose of the inquiry.
DR. MANISHA SETH

STATISTICS SHOULD BE COLLECTED IN A SYSTEMATIC
MANNER
 A suitable plan should be prepared for data collection and the work should be carried out in a systematic
manner. If the data are collected haphazardly, the conclusions may be wrong or miss leading.
DR. MANISHA SETH

STATISTICS SHOULD BE CAPABLE OF BEING PLACED IN
RELATION TO EACH OTHER
 The numerical data should be comparable, as statistics are collected mostly for the purpose of
comparisons. The numerical data collected constitutes statistics if they are comparable. In order to make
valid comparisons, the data should be homogeneous and uniform.
 For example, the export figure commodity for different years constitutes statistics as they are
comparable. But the height of a student and his intelligence quotient (I.Q) do not constitute statistics as
they are not comparable.
 Thus, we conclude that "All statistics are numerical statements of facts but all numerical
statements of facts are not statistics."
DR. MANISHA SETH

STATISTICS ARE AFFECTED TO A GREAT EXTENT BY A
MULTIPLICITY OF CAUSES
 Numerical figures should be affected by a large number of causes.
 For example, statistics of the production of a crop are affected by various factors s as the amount of
rain fall, quality of seeds, amount of fertilizer used, etc
DR. MANISHA SETH

STATISTICS ARE ENUMERATED OR ESTIMATED
ACCORDING TO REASONABLE STANDARDS OF ACCURACY
 Data may be collected either by actual counting and measurement or by estimation. The figures
obtained by counting and measurement will be exact and accurate but the figures estimated can not be as
accurate as those obtained by and measurement.
 The degree of accuracy of the estimated values largely depends on the nature and purpose of the
inquiry.
 For example, while measuring the height of the people, accuracy will be aimed in terms of a fraction of
an inch whereas in measuring the distance between two cities it may be in terms of km.
DR. MANISHA SETH

5 STAGES IN STATISTICAL INVESTIGATION
 1. Collection of data
 2. Organization
 3. Presentation (diagram ,graph )
 4. Analysis
 5. Interpretation
Statistics is a method of decision making in the face of uncertainty on the basis of numerical data and
calculated risk .
DR. MANISHA SETH

FUNCTIONS OF STATISTICS
1. It presents facts in a definite form
2. It simplifies mass of figures
3. It facilitates comparison
4. It helps in formulating and testing hypothesis
5. It helps in prediction
6. It helps in formulation of suitable policies
DR. MANISHA SETH

IMPORTANCE OF STATISTICS
 Statistics and planning
 Statistics and economics
 Statistics and business
 Statistics and industry
 Statistics and research
 Statistics and war
DR. MANISHA SETH

LIMITATIONS OF STATISTICS
1. Statistics is unable to explain individual items
2. Statistics are unable to study qualitative characters
3. Statistical results are not accurately correct
4. Statistics deal with average
5. Statistics is only one of the methods of studying a given problem
6. Statistics is liable to be misused
7. Qualitative Aspect Ignored
8. Many methods to study problems
9. Results are true only on average
10.Statistical laws are not exact
DR. MANISHA SETH

TWO BRANCHES OF STATISTICS USED IN BUSINESS
DR. MANISHA SETH

THESE TWO BRANCHES ARE USED IN THE IMPORTANT
ACTIVITIES
DR. MANISHA SETH

DESCRIPTIVE STATISTICS
DR. MANISHA SETH

INFERENTIAL STATISTICS
DR. MANISHA SETH

A STEP-BY-STEP PROCESS FOR EXAMINING AND
CONCLUDING FROM DATA ( DCOVA MODEL )
DR. MANISHA SETH

TYPES OF VARIABLES
DR. MANISHA SETH

COLLECTION
OF DATA
UNIT 1
DR. MANISHA SETH

DATA
Data constitute the foundation of statistical analysis and interpretation
Type of data
 Primary data
 secondary data
Sources of data
 Primary source
 Secondary source
Methods of collecting primary data and secondary data
DR. MANISHA SETH

STATISTICAL DATA
They are available in raw form called raw data
They are facts expressed numerically
They are descriptive
Meant for Processing and Processed data in decision
No sense without Application of Statistical Methods
DR. MANISHA SETH

SECONDARY DATA
DR. MANISHA SETH
The data prepared by highly skilled man powers is called "Secondary data".
In other words; the data which are initially collected by someone but obtained from some published
or unpublished sources are called "Secondary data". This data is not original in character.

METHOD OF SECONDARY DATA COLLECTION
 In this case, the investigator uses only those data which have already been collected and used by
others.
Secondary data can be collected from the following two sources:
1. Published Sources
2. Unpublished Sources
DR. MANISHA SETH

1. PUBLISHED SOURCES
1. Official publication published by
1. Government such as report of C.B.S (Central Bureau of Statistics).
2. Reports of International Organisation such as World Health Organisation, U.N.O.(United Nations
Organisation),
3. World Bank,
4. International Labour Organisation,
5. International Monetary Fund etc.
1. Non- governmental (i.e. private) publications, such as
1. Reports of N.G. O
• Publications of individual intellectuals and scholars.
• Financial and economic journals.
• Reports of trade associations, magazines, market reports etc.
DR. MANISHA SETH

UNPUBLISHED SOURCE
 All the informations may not be published but may be suitable for the purpose of investigation.
 An unpublished information may be useful to investigator for his conclusion.
 The sources of unpublished data are
• report of private offices
• hospital records
• material collected by researchers
• records of campus administrations etc.
DR. MANISHA SETH

PRIMARY DATA
DR. MANISHA SETH
The data collected for the first time by the investigator himself from the field of enquiry is called "primary data".
An investigator can collect using different methods for his own purpose of investigation.
Hence, the primary data is original in character.
For example, if an investigator wants to investigate the incomes of workers of all the companies of Country, then the d
(i.e. income) collected by the investigator himself or his representative, are called primary data.

METHOD OF PRIMARY DATA COLLECTION
 The following are the various methods of collecting primary data.
1. Direct personal contact
2. Indirect oral interviews
3. Mailed questionnaire
4. Questionnaire sent through enumerators
DR. MANISHA SETH

1. DIRECT PERSONAL CONTACT (INTERVIEWS)
1. In this method, the investigators (or, interviewer) collect data by personally contacting the respondents.
 Merits
1. Information collected by this method is more accurate
2. Responsibility of the data is very high
3. Extra supplementary information can be obtained which may help in drawing conclusion
4. Proper language and technique can be adopted according to the nature and status of the informant
5. Sensitive type of questions can be asked at such time only when the informants feel at home with the
interviewer
 Demerits
1. It consumes time and money
2. Accurate informations can not be obtained due to personal bias
3. This method is not applicable if the field of investigation is not narrow
4. The data will not be reliable if the interviewer is not well- trained, qualified and intelligent
DR. MANISHA SETH

2. INDIRECT ORAL INTERVIEWS
 In this method, the informations are collected by the interviewer from third person who are
directly or indirectly concerned with the informations to be collected.
 For example, in the study of the drinking (or smoking) habits of the society, one who drinks
(or smokes) is unable to give information of his bad habits. In this case, it is necessary to get
informations from those who may know him.
 In this method, the persons are selected on following basis:
• they should explain the full facts of the problem
• they should be capable of giving correct answers
• they shouldn't be personal biased.

DR. MANISHA SETH

2. INDIRECT ORAL INTERVIEWS
 Merits
1. It saves money, time and labour
2. A wide area can be taken as the field of investigation
3. The opinion and suggestion of experts can be solicited
 Demerits
1. Exact informations may not be obtained due to the doubtful information given by witnesses.
2. The investigator can twist the facts, if he is a biased person.

DR. MANISHA SETH

3. MAILED QUESTIONNAIRE
 In this method, a list of questions (i.e. questionnaire) relating to the investigation, is prepared and
sent by post to the various informants. The informants are requested to fill up the questionnaire
and is sent back to the enquiry office with the time mentioned. This method is suitable for the
regions where people are educated and cooperative.
 Merits
1. Real informations are obtained as the questionnaires are filled by informant.
2. Informations are obtained quickly and cheaply
3. If the informants are spread over a wide geographical area and the informations are to be
collected from wide area, then this method is suitable.
 Demerits
1. This method is suitable only for those regions where people are educated and cooperative.
2. Most of the questionnaires are not returned back by the informants due to their non-
responsibilities.
3. The results may not be accurate due to the misunderstanding of the given set of questions
DR. MANISHA SETH

4. QUESTIONNAIRE SENT THROUGH ENUMERATORS
 In this method, local agents (called enumerators) are appointed and trained properly. Then the questionnaires
are sent to the informants through the enumerators but not by post. The enumerators visit door to door along
with their questionnaires and the informations given by the informants are noted.
 The data collected by the enumerators are sent back to the investigator (or the office concerned) for further
processing of data. This method is usually suitable research organizations.
 Merits
1. This method is suitable even for uneducated informants
2. The chances of responsibility is high due to the personal contact between enumerator and informant.
3. Enumerators can ask some additional questions relating to the investigation
 Demerits
1. It is very labourous, expensive and time consuming method.
2. This method is not free from the biasness of the enumerators.
3. If the enumerators are not well - trained, the data collected may not be correct.


DR. MANISHA SETH

STATISTICAL METHODS
Helps in raw data Processing
It is a Process
It is a tool of Analysis
Helps in analyzing the processed data
It remains idle for the want of Statistical Data
DR. MANISHA SETH

PRESENTATION
OF DATA
UNIT 1
DR. MANISHA SETH

INTRODUCTION
 Data if presented in easy to read form , it can help the reader acquire knowledge in a much shorter
period of time and facilitate statistical analysis
 Presentation can take two basic forms
a) statistical table
b) statistical chart
DR. MANISHA SETH

I CLASSIFICATION OF DATA
 Classification is the grouping of related facts into different classes
 Broadly the data can be classified on the following four basis
1. Geographical i.e area wise for example cities , districts etc
2. Chronological i.e on the basis of time
3. Qualitative i.e according to some attributes
4. Quantitative i.e in terms of magnitudes
DR. MANISHA SETH

II. TABULATION OF DATA
 A table is a systematic arrangement of statistical data in columns and rows.
 The purpose of a table is to simplify the presentation and to facilitate comparisons
 The simplification results from the clearcut and systematic arrangement which enables the reader
to quickly locate desired information .
DR. MANISHA SETH

III CHARTING DATA
DR. MANISHA SETH

MEASURES OF
CENTRAL
TENDENCY
UNIT 1
DR. MANISHA SETH

OBJECTIVES OF AVERAGING
 To get one single value that describes the characteristics of the entire data
 To facilitate comparison
DR. MANISHA SETH

CHARACTERISTIC OF A GOOD AVERAGE
 it should be easy to understand
 it should be simple to compute
 it should be based on all the observations
 it should be rigidly defined
 it should be capable of further algebraic treatment
 it should have sampling stability
 it should not be unduly affected by the presence of extreme values
DR. MANISHA SETH

STATISTICS INTRODUCTION A.pptx

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STATISTICS INTRODUCTION A.pptx