This document discusses the process of data processing, analysis, and interpretation. It describes the key steps as: 1) data preparation through editing, coding, and entry; 2) data processing by editing, coding, classifying, transcribing, and tabulating the data; and 3) statistical analysis to summarize and examine relationships in the data. The main steps in processing include identifying data structures, editing for accuracy, coding responses numerically or alphabetically, classifying open-ended responses, transcribing to a spreadsheet, and tabulating the data through frequency tables for further analysis.

1. PROCESSING, ANALYSIS & INTERPRETATION
OF DATA

2. MEANING
Data preparation to arrive at a meaningful research
analysis. Intermediary b/w data collection & data
interpretation
Data preparation consist of 3 important steps:
1. Editing
2. Coding
3. Data entry

3. DATA PROCESSING
Processing implies editing, coding, classification &
tabulation of collected data so that they are amenable to
analysis
Analysis refer to the computation of certain measures

4. STEPS IN PROCESSING DATA
Identifying data structures
Editing
Coding & Classifying
Transcription
Tabulation

5. 1)Identifying Data Structures
Defining data structure to use modern analysis
software such as SPSS.
A data structure is a dynamic collection of related
variables that can be represented as graph.
It defines relationship b/w variables /groups.

6. 2)Editing
Editing is the review of the questionnaire with the objective of
increasing accuracy and precision.
It is needed to detect and if possible to eliminate errors in the
filled questionnaires.
It involves a careful scrutiny of the completed questionnaires
and /or Schedules
There are three points--- completeness, accuracy and uniformity,
to be checked while editing the data.

7. 3)Coding
The purpose of coding in surveys is to put the answers into a
particular question into meaningful and unambiguous categories
to bring out essential pattern, concealed in the mass of
information
Coding refers to the process of assigning numerals or other
symbols to answers
Coding can be of:
1. Numeric coding is compulsory when the variable is to be subject
to further analysis Egs: Yes – 1, No - 2
2. Alpha numeric coding- given for table or graph
3. Zero Coding – to be given carefully for missing value or no
response

8. Classification
Arranging data in groups or classes according to
similarities in characteristics
Required especially for open ended responses.
All possible response types to be considered.
Data arranged according to resemblance, affinities,
common characteristics

9. 4) Transcription of Data
Transferring data collected on to a data sheet with
summary of all responses.
Aim is to minimize shuffling of pages b/w responses
& observations.
Transcription helps in presentation of all responses . It
is an intermediary process b/w coding and tabulation.
Can be manual for small data sets
Excel sheets can be used in transcription of large data
sets. – observations as rows and responses as columns.

10. 5) Tabulation
Process of summarizing raw data in a compact form
and displaying them in statistical tables for further
analysis.
Manually simple frequency tables can be constructed
by counting the yes and no responses.
Computer tabulation with s/w packages as SPSS –
Statistical Package for Social Science Data input
requirement will be column & row variables.

11. STATISTICAL ANALYSIS
examination of the assembled and grouped data
studies the characteristics of the object under study
determines the patterns of relationships among
variables relating to it

12. PURPOSE OF STATISTICAL ANALYSIS
 summarizes data into understandable and
meaningful form
 makes exact descriptions possible
 facilitates identification of causal factors
 aids the drawing of reliable inferences from
observational data

13. Approach to Statistical Analysis
descriptive analysis: construction of statistical
distribution and calculation of simple measures like
averages, percentage and measures of dispersion -
mean, median, mode.
compare two or more distribution or two or more sub-
groups within a distribution – Ratios, proportions and
percentages.
study the nature of relationship among variables-
correlation & regression.