interpretation of data

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.