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Reliability test ? Descriptive statistics for demographics with graphs ? Descriptive statistics for variables with graph

  1. Reliability test
     
  2. Descriptive statistics for demographics with graphs
     
  3. Descriptive statistics for variables with graphs
     
  4. Multiple regression results – providing explanation for the results, explaining which numbers we have to look at and what they mean and which hypotheses were supported and which hypotheses are rejected
     

Based on a provided SPSS dataset, this individual work covers: written report according to SPSS analysis and interpretation of data provided.

  1. Check the questionnaire and the data in your dataset, variable view. Take respective actions.

     

  2. Add the missing respective coding in the word document, which are highlighted in yellow.
     
  3. Code all of the variables/questions in your variable view with the appropriate codes mentioned in the word document in order to make the analysis easier. E.g. Q6 is measuring normative interpersonal influences so you can code it as Q6_1_NII, Q6_2_NII, Q6_3_NII etc.
     
  4. After creating the codes, you will need to reverse item: Q6_6 [6. I never identify with other people by not purchasing the same luxury products and brands they purchase.]. Recode this into a different variable. – make sure the equations are shown in your output file.
     
  5. Then you need to test the reliability for all the variables: normative interpersonal influences, hedonic value, informational interpersonal influences, need for uniqueness, product quality, perceived value, brand attitude, purchase intentions. – make sure these results are both in the output file and in the word document file. Explain which numbers we have to look at and what they mean.
     
  6. Create the averages for all the variables that are in the conceptual model based on your reliability scores – make sure the equations are shown in your output file. Name the target variables as e.g.
     
  7. Do the descriptive statistics for the demographics (age, gender, education, income) and use different graphs – make sure these results are both in the output file and in the word document file. Describe the results.
     
  8. Do the descriptive statistics for the variables in your conceptual model – make sure these results are both in the output file and in the word document file. Describe the results.
     
  9. Run a multiple regression for your conceptual model VERSION 1 and report the results. You will need to interpret the results explaining which numbers we have to look at and what they mean, which hypotheses are supported, and which hypotheses are rejected – make sure these results are both in the output file and in the word document file. In the word document, you need to also write the explanations of the results, what they mean and the hypotheses supported or rejected.
     
  10. Run two multiple regressions for your conceptual model VERSION 2 and report the results. You will need to interpret the results explaining which numbers we have to look at and what they mean, which hypotheses are supported, and which hypotheses are rejected – make sure these results are both in the output file and in the word document file. In the word document, you need to also write the explanations of the results, what they mean and the hypotheses supported or rejected.

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