Sarfraz Ahmad Lecturer KUST Kohat

1. Collection
and
Editing of Data

2. Collection of Data
Statistical Data:
A sequence of observation, made on a
set of objects included in the sample drawn
from population is known as statistical data.

3. Collection of Data
Forms of Data
1. Ungrouped Data:
Data which have been arranged in a
systematic order are called raw data or
ungrouped data.
2. Grouped Data:
Data presented in the form of
frequency distribution is called grouped
data.

4. Collection of Data
Collection of Data:
• The first step in any enquiry (investigation) is
collection of data.
• The data may be collected for the whole
population or for a sample only.
• It is mostly collected on sample basis.
• Collection of data is very difficult job.
• The enumerator or investigator is the well
trained person who collects the statistical data.
• The respondents (information) are the
persons whom the information is collected.

5. Collection of Data
Types / Sources of Data
• There are two types (sources) for the
collection of data.
(1) Primary Data
(2) Secondary Data

6. Collection of Data
(1) Primary Data:
• The primary data are the first hand
information collected, compiled and published by
organization for some purpose.
• They are most original data in character and
have not undergone any sort of statistical
treatment.
• Example: Population census reports are
primary data because these are collected,
complied and published by the population census
organization.

7. Collection of Data
(2) Secondary Data:
• The secondary data are the second hand
information which are already collected by
some one (organization) for some purpose
and are available for the present study.
• The secondary data are not pure in
character and have undergone some
treatment at least once.

8. Collection of Data
Example:
• Economics survey of England is
secondary data because these are collected
by more than one organization like Bureau of
statistics, Board of Revenue, the Banks etc…

9. Collection of Data
Methods of Collecting Primary Data:
Primary data are collected by the following
methods:
1. Personal Investigation:
The researcher conducts the survey
him/herself and collects data from it. The data
collected in this way is usually accurate and
reliable. This method of collecting data is only
applicable in case of small research projects.

10. Collection of Data
Methods of Collecting Primary Data:
2. Through Investigation:
Trained investigators are employed to collect
the data. These investigators contact the
individuals and fill in questionnaire after asking
the required information. Most of the organizing
implied this method.

11. Collection of Data
Methods of Collecting Primary Data:
3. Collection through Questionnaire:
The researchers get the data from local
representation or agents that are based upon
their own experience. This method is quick but
gives only rough estimate.
4. Through Telephone:
The researchers get information through
telephone this method is quick and give accurate
information.

12. Collection of Data
Methods of Collecting Secondary Data:
The secondary data are collected by the following
sources:
1. Official: e.g. The publications of the Statistical
Division, Ministry of Finance, the Federal Bureaus
of Statistics, Ministries of Food, Agriculture,
Industry, Labor etc…
2. Semi-Official: e.g. State Bank, Railway Board,
Central Cotton Committee, Boards of Economic
Enquiry etc…

13. Collection of Data
Methods of Collecting Secondary Data:
3. Publication of Trade Associations, Chambers of
Commerce etc…
4. Technical and Trade Journals and Newspapers.
5. Research Organizations such as Universities and
other institutions.

14. Collection of Data
Difference between Primary and Secondary Data:
• The difference between primary and secondary
data is only a change of hand.
• The primary data are the first hand data
information which is directly collected form one
source.
• They are most original data in character and
have not undergone any sort of statistical treatment
while the secondary data are obtained from some
other sources or agencies.
• They are not pure in character and have
undergone some treatment at least once.

15. Collection of Data
For Example:
• Suppose we interested to find the average
age of MS students.
• We collect the age’s data by two methods;
either by directly collecting from each student
himself personally or getting their ages from the
university record.
• The data collected by the direct personal
investigation is called primary data and the data
obtained from the university record is called
secondary data.

16. Data Editing

17. Data Editing
Definition
• It is defined as the process involving the
review and adjustment of collected survey
data.
• The purpose is to control the quality of
the collected data.
• Data editing can be performed
manually, with the assistance of a computer
or a combination of both.

18. Data Editing
1. Editing methods
1.1. Interactive Editing
1.2. Selective Editing
1.3. Macro Editing
1.3.1. Aggregation Method
1.3.2. Distribution Method
1.4. Automatic Editing

19. Data Editing
1.1. Interactive Editing
• The term interactive editing is commonly
used for modern computer-assisted manual
editing.
• Most interactive data editing tools applied at
National Statistical Institutes (NSIs) allow one to
check the specified edits during or after data entry,
and if necessary to correct erroneous data
immediately.

20. Data Editing
1.1. Interactive Editing
Several approaches can be followed to
correct erroneous data:
a) Re-contact the respondent
b) Compare the respondent's data to his
data from previous year
c) Compare the respondent's data to data
from similar respondents
d) Use the subject matter knowledge of
the human editor

21. Data Editing
1.1. Interactive Editing
Several approaches can be followed to
correct erroneous data:
e) Interactive editing is a standard way to edit
data.
f) It can be used to edit
both categorical and continuous data.
g) Interactive editing reduces the time frame
needed to complete the cyclical process of
review and adjustment.

22. Data Editing
1.2. Selective Editing
a) Selective editing is an umbrella term for
several methods to identify the influential
errors, and outliers.
b) Selective editing techniques aim to apply
interactive editing to a well-chosen subset of
the records, such that the limited time and
resources available for interactive editing are
allocated to those records where it has the
most effect on the quality of the final
estimates of publication figures.

23. Data Editing
1.2. Selective Editing
c) In selective editing, data is split into two
streams:
1. The critical stream
2. The non-critical stream
1. The critical stream consists of records that are
more likely to contain influential errors. These
critical records are edited in a traditional
interactive manner.

24. Data Editing
1.2. Selective Editing
2. The records in the non-critical stream which
are unlikely to contain influential errors are not
edited in a computer assisted manner.

25. Data Editing
1.3. Macro Editing
1.3.1. Aggregation Method
1.3.2. Distribution Method

26. Data Editing
1.3. Macro Editing
1.3.1. Aggregation Method
• This method is followed in almost
every statistical agency before publication:
verifying whether figures to be published
seem plausible.
• This is accomplished by comparing
quantities in publication tables with same
quantities in previous publications.

27. Data Editing
1.3. Macro Editing
1.3.1. Aggregation Method
• If an unusual value is observed, a
micro-editing procedure is applied to the
individual records and fields contributing to
the suspicious quantity.

28. Data Editing
1.3. Macro Editing
1.3.2. Distribution Method
• Data available is used to characterize
the distribution of the variables.
• All individual values are compared with
the distribution.
• Records containing values that could be
considered uncommon (given the
distribution) are candidates for further
inspection and possibly for editing.

29. Data Editing
1.4. Automatic Editing
• In automatic editing records are edited by a
computer without human intervention.
• Prior knowledge on the values of a single
variable or a combination of variables can be
formulated as a set of edit rules which specify or
constrain the admissible values.

30. Thank You