I have carried out an evaluation of a product using likert scale questionnaire and imported the date into SPSS. I have my columns arranged as follows:
ID, Group, Q1, Q2, Q3, Q4
I have two different groups completing the questionnaire, with each person a different numerical ID. Under the Q columns, I have the score given for that person (from 1-5) from the Likert Scale.
In all there are over 300 responses.
I am running analysis using 'descriptive statistics/frequencies' from the menubar and not getting the tables I am looking for. Basically, it is including all respondents together, whereas I would like it to compare the two groups in the tables.
How can I get descriptive statistics on questionnaire items by group using SPSS?
In addition, if you have any further tips as to what analysis I could perform on this type of data in SPSS I'd be most grateful. I'd like to show that there isn't a significant difference in opinions between the groups, and from looking at the data, it appears that this is the case.
One option
See this SPSS FAQ item from UCLA on how to analyze data by categories.
The short answer to you question is, crosstabs Q1 to Q4 by group.
will produce the table you want. Or if you have the ctables
package available a more compact table will be produced by
variable level group_id Q1 to Q4 (nominal).
ctables
/table Q1 + Q2 + Q3 + Q4 by group_id.
Either can be elaborated on to produce other statistics if wanted. It seems to me a chi-square test would be sufficient for your question.
As far as further analysis it is a bit of an open-ended question that needs more focus to be able to effectively answer. I frequently suggest visual exploration for such exploratory analysis, and hence I would suggest perusing this question on the site, Visualizing Likert responses using R or SPSS for potential ideas about how to visualize the responses. Another motivating post may be How to visualize 3D contingency matrix?.
There are a ton of other questions related to analyzing likert responses on this site though, and it is difficult to give any more specific advice without a more specific motivation for the analysis.
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