The market for tablet PCs has expanded at an incredible rate over the last few years. The reasons for this are numerous, however low prices and the availability of new technology mean that even children now own and regularly use tablet PCs.
A number of companies are now offering tablet PCs. The marketing manager of a major tablet PC manufacturer wants to get an insight into the attitudes and behaviour of tablet PC users. The primary purpose of the survey was to ascertain what customers take into account when choosing a tablet PC and what determines their satisfaction with the product. In October 2012, a questionnaire was mailed to a random sample of 1,000 tablet PC users drawn from the customer database. To increase the return rate, a small prize draw of Amazon vouchers was used. To avoid sampling bias, a stratified sampling methodology was employed for both age and gender, as defined by the demographic make-up of the UK population. The SPSS data set which is named ?
The data analysis section of your research report should provide the following information:
1. Provide a short demographic profile of the respondents.
2. Provide some key findings for the survey using descriptive statistics only (e.g. frequencies, means). Note: analyse the general information about tablet PC usage, e.g. type of tablet PC, brand, cost etc.
3. Analyse whether gender has any significant effects on recommendation, emotions, tablet PC brand purchased and style influence. (Note: different analyses will be required depending on the level of measurement of the variables)
4. Carry out two factor analyses separately for the following variables: Importance questions (Importance1 to Importance 8) and satisfaction questions. Interpret and name the new factors and test the reliability for each new factor. Report the results for these. Save the factor scores or newly computed variables (e.g. means calculated for the new factors) for further analysis.
5. Is there a significant relationship between age, satisfaction (new factor), importance (new factors), emotions and loyalty? Using evidence from the data set, discuss whether there is a possibility of predicting loyalty on the basis of satisfaction, age and emotions? What is a better predictor of loyalty ? emotions or satisfaction?
6. Are there any additional interesting findings from the dataset which might be relevant in this research context? If you have carried out any additional analyses which are of interest to the research question, please add your results at the end of the report. Note: this could be additional descriptive results or analysis of significant differences between types of customer and importance and satisfaction etc. Only report significant results and findings which are of interest to the marketing manager.