Basic Concept of Collection and Presentation of Business Data

Introduction of Statistics
Bipul Kumar Sarker
Lecturer
BBA Professional
Habibullah Bahar University College
Chapter-01

Definition of Data
Bipul Kumar Sarker, Lecturer (BBA Professional), HBUC
Data are the collection of any number and raw facts of related
observation.
• Types of Data:
In Statistics data are of two kinds:
 Qualitative data
 Quantitative data

Types of Data
Qualitative data:
The data which can not be measured by the numerical form is called
qualitative data.
Some examples of qualitative data are given below:
 Religion, Economical condition, Color, Sex etc

Types of Data
Quantitative data:
The data which can be expressed in numerical form or in number is
called quantitative data.
Some examples of qualitative data are given below:
 Family Size, Population Size, Height, Weight, Monthly Income etc

Sources of Data
According to source data can be classified into two categories:
 Primary Data
 Secondary Data

Sources of Data
Primary Data:
The data which are obtained by direct observations from the
population or sample is called primary data.
Primary data are also called raw data. The collection of
raw data is highly expensive in respect of money, time and labor.

Sources of Data
Secondary Data:
The data which are obtained by some other persons or
organizations and are already published or utilized are called
secondary data.

Methods of Primary Data Collection
 Direct personal observation
 Indirect oral interview
 Information through agencies
 Mailed questionnaires
 Schedules sent through enumerator

Advantages of Primary Data
 Degree of accuracy is quite high
 It does not require extra care
 It depicts the data in great detail
 Primary source of data collection frequently includes
definitions of various term and units used
 For some investigations, secondary data are not available

Advantages of Secondary Data
 Secondary data if available, can be secured quickly and cheaply
 The use of secondary data enables a researcher to verify the
findings based on primary data

Disadvantages of Secondary Data
 The most important limitation is the available data may not
meet, our specific research needs.
 The available data may not be as accurate as desired.
 The secondary are not up-to-date

Sources of Data
The various sources of secondary data can be divided into
two categories:
 Published Sources
 Unpublished Sources

Sources of Data
Published Sources:
 International Publications
• Such as, IMF, WB, UNO,WFO etc
 Government and Semi-Government Organization
• Such as, City Corporation, District Council etc

Sources of Data
Published Sources:
 Commercial Organization
• Such as, Dhaka Chamber of Commerce Industries
(DCCI), Dhaka Stock Exchange (DSC) etc
 Research Institutes
• Such as, Bangladesh Institute of Development
Studies , (DIDD), Bangladesh Agricultural
Research Institute (BARI) etc

Sources of Data
Unpublished Sources:
There are various sources of unpublished data. They are the records
maintained by various government and private offices, the researches
carried out by individual research scholars in the universities or
research institutes.

Difference between primary data and Secondary Data
There are the following difference between primary data and secondary data:
Primary data Secondary data
Primary data are those which are
collected for the first time.
Secondary data are those which are
already collected by someone tor some
purpose and are available for present
study
Primary data are collected from the
original sources
Secondary data are not collected from
the original sources
It is more reliable than secondary data Secondary data is less reliable than
primary data
Primary data is completely independent Secondary data depend on primary data

Classification of Data
Definition of classification :
Classification is a process of arranging the available
information's into homogeneous groups according to similarities or same-
characteristics.
According to L.R. Connor,
The process of arranging things in groups or classes according to
resemblance and affinities.

The data can be classified into the following types:
a) Geographical classification
b) Chronological classification
c) Quantitative classification
d) Qualitative classification

Geographical Classification :
In geographical classification the are classified on the basis of
geographical areas.
For example:
The production of the different division wise of Bangladesh is given below:
Division Dhaka Chittagong Rajshahi Khulna Barisal Rangpur
Production (In
tonnes)
1572 865 1464 1602 2038 1623

Quantitative Classification:
In quantitative classification data are classified in terms of
magnitudes.
For example:
The marks obtained by the BBA Professional students in Statistics.
Marks Distribution 50-60 60-70 70-80 80-90 90-100
Marks Obtained 26 6 5 2 1

Qualitative Classification:
In qualitative classification data are classified in terms of some attributes.
For example:
The classification according to the religion and gender of BBA Professional
students of a college are given below.
Religion Gender
Male Female
Hindu 1 0
Muslim 26 17

Properties or Characteristics of a good classification of data
 Un-ambiguousity
 Stability
 Flexibility
 Ideal number of class

Importance of classification of data
 Classification facilitates comparisons and makes calculations easier
 As classification classified the data evidently, there rests no chance for
overlapping
 After classification it is easier to tabulation

Tabular Representation
Definition of tabulation:
A statistical table is the orderly and logical listing of a
quantitative data where the numbers of information are arranged in
rows and columns.
Here rows are horizontal arrangements and columns are vertical
arrangements.

Definition of Data

Basic Concept of Collection and Presentation of Business Data

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Basic Concept of Collection and Presentation of Business Data