In my Questionnaire, There are 5 main factors. There are 6 questions in each factor. All questions in 5 ringgit scale (Strongly agree, Agree, Neutral, Disagree and Strongly Disagree).I need to combines all 6 questions as one for each Factor.
Because i need to know about my each factors.
Can anyone explain using SPSS.
The first order of business is to test each set of 6 questions for reliability (consistency) i.e. by means of Cronbach's alpha. (analyse - scale - reliability). If the Cronbach alpha is satisfactory (some authors say 0.6 is satisfactory while 0.8 is good). If the alpha value is acceptable, you may calculate a factor score for each factor as the average of the six items (Transform - compute - Score=(Q1+Q2+Q3+Q4+Q5+Q6)/6.)
If my average value is 2.5, What is means.
Because i fix 2 for Disagree and 3 for Neutral.
What can i do now..?
which option i need to select in Transform - Compute - then which option?????...
If i got decimal value as Average, What it means..?
If you click on TRANSFORM - COMPUTE VARIABLE then it will ask you for a TARGET VARIABLE and an EXPRESSION. For the target variable you choose a name (I used SCORE in my example, but you could use FACTOR1 for the first of your five factors, then FACTOR2 for the second one etc.) For the EXPRESSION you click on (), then move the cursor between the brackets, move the first question of Factor 1 into the expression block, type +, move the second question into the expression block etc. When the six questions have been entered into the expression block, move the cursor outside the closing bracket and type /6, then OK.
If the score (i.e. the average) is 2.5 (or 2.5167 for that matter) it means the majority of respondents were on the "Agree" side of Neutral, i.e. there was more Agreement than Disagreement by the respondents. The score is just a number, you do not need to attach a particular meaning to it. The scores can be used to compare group means (e.g. compare male and female respondents using a t-test or Senior Management, Middle Management and Junior Management using ANOVA).
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