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:
Editing
Coding
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:
Numeric coding is compulsory when the variable is to be subject to further analysis Egs: Yes – 1, No - 2
Alpha numeric coding- given for table or graph
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.