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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.

David
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4 Answers4

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One option

  • split file by group
  • run descriptive statistics as usual

See this SPSS FAQ item from UCLA on how to analyze data by categories.

Jeromy Anglim
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    (+1) I forgot to mention that descriptive stats for continuous variables are not available via crosstabs. Also the `EXAMINE` command via the menu's `Analyze -> Descriptives -> Explore` can produce descriptive stats by groups, but the split file approach is much less verbose an output to parse. – Andy W Jun 15 '12 at 11:51
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    I would also suggest to the OP to check out Jeromy's [responses to questions tagged Likert](http://stats.stackexchange.com/search?q=user:183+[likert]), it looks like on the first page there are numerous related topics. See for instance [What are good basic statistics to use for ordinal data?](http://stats.stackexchange.com/q/97/1036). – Andy W Jun 15 '12 at 11:54
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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.

Community
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Andy W
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While the above answers all have their good points, I usually prefer this procedure (type the following into a syntax window and Run):

means q1 to q4 by group/stat anova.

This will give you group means, sample sizes, and standard deviations as well as tests of the difference in means between the groups, for each of the variables Q1 to Q4. Of course, the tests will only give you valid results to the extent that your data meet the standard assumptions of anova. Some may say that variables measured on an ordinal 1-5 scale are not suitable for anova, and in academic contexts this is often true, but in business contexts most people are willing to sacrifice some rigor for the sake of convenience. It's much more convenient to compare 4x2=8 means than it is to compare the distributions of 4x5x2=40 categories of responses.

rolando2
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This can easily be done by using the "Crosstabs" function in SPSS for Windows:

Analyze --> Descriptive Statistics --> Crosstabs. Move the dependent variable(s) into the "Row(s)" box, then move the grouping variable into the "Column(s)" box, then click OK.