tribhuvan University M.A population Studies Research methods for population analysis Data Processing, editing and coding if any mistakes, suggest me to improve it. thank you hope its useful for all :)

1. Data Processing, Editing and
Coding
By: Roji Maharjan
M.A Population Studies
Research Methods For Population Anlaysis
Padma Kanya Multiple Campus, Bagbazar
2078/02/26

2. Objectives:
To describe data processing with steps and methods
To define editing with its purposes
To describe coding with process

3. Introduction:
Research is a process of systematic inquiry that entails
collection of data; documentation of critical information,
analysis and interpretation of that data/information, in
accordance with suitable methodologies as per discipline.
creates new knowledge and/or the use of existing knowledge
in a new and creative way so as to generate new concepts,
methodologies and understandings.
Important and crucial in every field.
Carried out with definite procedure for better result.
One of the process is data processing, editing and coding
which helps to organize, integrate, corrects, simplify, verify,
transform and extract data to appropriate output.

4. Data Processing:
Data in its raw form is not useful to any organization. So it
requires processing; converted and translated into usable
information.
Data processing is the method of collecting raw data and
translating and converting it into usable information and desired
form.
The essence of data processing in research is data reduction which
involves winnowing out the irrelevant from the relevant data and
establishing order from chaos and giving shape to a mass of data.
Carried out using a predefined sequence of operations either
manually or automatically.
Series of steps in cyclic manner is carried out where raw data is
processed to get desirable form of data.

5. Steps of data processing
Data Collection: gathered from defined and
accurate sources so that the subsequent findings are
valid and usable.
Data preparation: process of sorting and filtering
raw data to remove unnecessary and inaccurate data.
Data input: converted into machine readable form
and fed into the processing unit.
Data Processing: subjected to various methods to
generate a desirable output.
Data output/ Interpretation: transmitted and
displayed to the user in a readable form
Data storage: stored for further use.

6. Methods of data processing
1. Manual data processing: processed manually without using any
machine or tool to get the required results.
2. Mechanical data processing: uses different devices like
typewriters, mechanical printers or other mechanical devices.
3. Electronic data processing: uses the computers (software like
MS Excel, SPSS) to collect, manipulate, record, classification
and to summarize data.
In data processing: Scrutinizing (examine in detail), data entry
(inputs data) , checking (examine accuracy and quality) and
updating (change) is carried out.
Involves editing, coding, tabulation, classification and
presentation.

7. Data editing:
The process of examining and adjusting the data collected in
questionnaires/schedules to detect errors and omissions,
legibility, consistency and readying them for coding and storage.
Detects errors and omissions, corrects them when possible and
certifies that minimum data quality standards are achieved.
 Done to assure:
1. Accuracy of data collected
2. For consistency between responses
3. Uniformity
4. For completeness in responses
5. To facilitate and Simplify coding and Tabulation.
6. To better utilize questions answered out of order

8. Types of editing:
Field editing:
It is done by the enumerator or a field supervisor on the
same day as the interview to catch technical omissions,
check legibility of handwriting, and clarify responses that
are logically or conceptually inconsistent.
In-house or Central editing:
It is done by the researcher or a central office staff after
getting all schedules or questionnaires or forms from the
enumerators or respondents to correct Obvious errors;
often done more rigorously than field editing.

9. Points to remember by editor during editing:
familiar with instructions and codes given to the interviewers and
coders and the editing instructions supplied to them for the purpose,
While crossing out an original entry for a reason, they should just
draw a single line on it so that the same may remain legible,
They must make entries on the form in some distinctive color and
that too in a standardized form,
They should initial all answers which they change or supply,
Editor’s initials and the data of editing should be placed on each
completed form or schedule.
The date of editing may also be recorded on the schedule for any
future references.

10. Data Coding:
The process of identifying, classifying and assigning each answers
with some symbols (alphabetical or numerals) so that the responses
can be recorded into a limited number of classes or categories.
Necessary for efficient analysis and through it the several replies
may be reduced to a small number of classes which contain the
critical information required for analysis.
The coding decisions should usually be taken at the designing stage
of the questionnaire itself so that the likely responses to questions
are pre-coded and simplifies computer tabulation of the data for
further analysis.
serves as a rule for interpreting, classifying, and recording data.

11. guides the establishment of category sets: Appropriate to the
research problem and purpose, Exhaustive , Mutually exclusive,
Derived from one classification principle.
Process:
1. Set the Rules For Code Construction: Coding categories
should be exhaustive or mutually exclusive and independent.
2. Pre-Coding Fixed-Alternative Questions (FAQs) - Writing
codes for FAQs on the questionnaire before the data collection.
Coding Open-Ended Questions - A 3-stage process: Perform a
test tabulation, plan a coding scheme, Code all responses.
3. Maintaining a Code Book: identifies each variable in a study,
the variable’s description, code name, and position in the data
matrix.

12. Data Matrix: a works sheet with coded data in a rectangular
form with data in rows and columns representing cases and
variables. The data matrix is organized into fields, records and
files.
4. Production Coding: The physical activity of transferring the
data from the questionnaire or data collection form [to the
computer] after the data has been collected.
5. Combining Editing and Coding: Finally the coding and
editing is combined for further analysis.
 After editing and coding further process of data processing
are carried out to get the raw data in the usable format and to
use it in efficient way.

13. Conclusion:
Data processing is concerned with editing, coding,
classifying, tabulating and charting and diagramming
research data which involves winnowing out the irrelevant
data and establishing order to provide usable format for
completeness and efficiency of research data.
Comprises the process like editing, coding, classification
of data, data entry, updating data and providing required
outcome.
Crucial and essential function in research to provides the
base for the interpretation and analysis of data and to draw
out the outcome of the research.

14. Thank You !!