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1 To what extent can treating codes allocated to ordered category measures as if they are numeric values be justified in the data analysis process?

2 When transforming variables, researchers make many decisions for which there are no ‘rules’ or even rough guidelines. What impact might these decisions have on the validity of the data?

3 What are the key circumstances in which missing values might be a severe problem for the data analyst?

4 Open IBM SPSS on whatever system you are using and enter the nine key variables for the first 12 cases for the alcohol marketing dataset that are illustrated in the next chapter in Figure 3.1. The procedures for doing so are explained in Box 2.1.

5 Figure 2.10 shows the total scores for the importance of well-known brands in choosing products. Try creating class intervals in various different ways using SPSS. The procedures for doing so are explained in Boxes 2.2 and 2.3.

6 Go to the website www.surveyresearch.weebly.com. Here you will find lots of interesting information about social surveys created by John Hall, previously Senior Research Fellow at the UK Social Science Research Council (1970–6) and Principal Lecturer in Sociology and Unit Director at the Survey Research Unit, Polytechnic of North London (1976–92). Download the Trinians dataset. Select Survey Unit, Social Science Research Council, then Surveys by SSRC Survey Unit and then the ‘Trinians’ survey. Read the background to the survey, download the article in Folio and the questionnaire. Finally download and save the dataset from trinians.sav onto your SPSS file. Not all the questions in the questionnaire appear as variables and they are not all in the same order as in the questionnaire, but the question numbers are clearly marked. Check out the values being used from the Values column. Under Measure, they are all indicated as Scale. This is the default if researchers do not change any of these. Go down the variables and change to Ordinal or Nominal as appropriate (left click on Scale and the other two options will appear).