1. DATA ANALYSIS AND INTERPRETATION

2. Getting Data Ready for Analysis Editing Data Open-ended questions Questionnaire data have to be checked for incompleteness and inconsistencies

3. Getting Data Ready for Analysis (Cont’d) Handling blank responses If substantial number of questions have been left unanswered: throw out the questionnaire If only few items are left blank: Use midpoint Allow the computer to ignore the blank responses Mean value of responses of all those who have responded to that particular item Mean of the responses of this particular respondent to all other questions measuring this variable Random number

4. Getting Data Ready for Analysis (Cont’d) Coding Use coding sheet first Categorization Set up a scheme for categorizing variables such that several items that measuring a concept are all grouped together Entering data

5. Data Analysis Feel for the data Mean, range, standard deviation, variance Testing goodness of data Reliability Validity Hypothesis testing