Reference no: EM132389620

Question -

Continuing our work with time series data choose a company from the Company Revenue excel file in Doc Sharing and then choose two macroeconomic variables for Macro Data file in Doc Sharing that should represent the economic conditions that the company faces. Enter the data in columes that you title for each variable in the Minitab worksheet.

Go to Stat/Basic Statistics/Correlation in minitab and enter the company revenue column title followed by each of the X variable titles. Be sure to check Pairwise correlation table under the Results tab. Comment on the correlations. Are they relatively high or low? Note the XX variable correlation. Is it higher than the XY correlations?

Next, the Go to Stat/Time Series/Time Series Plot and select Simple from the menu options. Enter all three of your variables (revenue and two macro variables) and note the trend, cycle and seasonality (if any) in each variable time series plot.

Next, go to Stat/Time Series/Autocorrelaltion and run the Autocorrelation Functions (ACFs) for each of these three variables. Note if you see T, C or S in the ACF plots and explain how it shows up in the plots and if they support your time series plot assessment of T, C and S.

Finally, note the T, C and S characteristics if any that the two macroeconomic variable's data share with the revenue data.

Class Critical Research Evaluation Suggested Points -

1. What is the clear purpose of the research?

2. Who are the researchers and do they have a quantitative background?

3. What is the researcher's hypothesis? Is it focused and clear?

4. What are the data variables analyzed? What is the objective or response (Y) variable? What are the independent or X variables in the analysis?

5. Was the target population of the objective variable infinite or finite?

6. Was the study experimental or observational?

7. Was the data collected cross-sectional or time series?

8. Are the study data Ratio or Interval, Ordinal or Nominative?

9. What Sampling technique was used?

a. Stratified Random Sampling

b. Cluster Sampling

c. Systematic Sampling

10. Was the sampling probability or convenience sampling?

11. Was there sampling under-coverage relative to population members excluded

12. If surveys were used what type. Were they Phone, Mail, Web, Interview?

13. Was there significant non-response in sampling?

14. What was done to prevent potential data sampling response bias and sampling or recording error?

15. Was a random sample done with or without replacement?

16. Was the sample size adequate to determine analysis reliability?

17. What data analysis was performed to determine data characteristics and distribution? E.g. time series plots, histograms, bar charts, ogive charts?

18. Does the researcher describe objective data sample mean, median or mode?

19. Did the researcher determine if the objective data was skewed and not normally distributed?

20. Did the analyst describe the modality of the data - is it multimodal, bimodal?

21. Does the analyst describe the Range of the sample data, variance of the sample or the standard deviation of the sample data?

22. Do the variables in the researcher's hypothesis reliably describe the objective variable/s variation? If so at what confidence level?

23. Does the researcher mention potential data outliers?

24. What are the covariance and correlations of the sample independent variables to the objective dependent variable? Are they provided?

25. What are the directions of the relationship between each of the sample independent variables (Xs) and the objective (Y) variable?

26. Does the researcher describe the linear relationship between each X variable and the objective variable Y? Does the researcher provide the slope and intercept of the linear relationship? Note this relationship may be determined to be non-linear and the researcher must state this if it is so.

27. Did the analyst use factor analysis in the research (see Chapter 3.10)

28. Did the researcher quantitatively determine the accuracy of the analysis (Mean squared error, Root Mean Squared Error, Mean absolute percent error)?

29. Did the researcher provide information on the analysis error terms relative to information omitted from the model or research algorithm? (E.g. what was omitted in their quantitative analysis model or algorithm.)

30. In what manner did the researcher determine analysis reliability or confidence in the analysis results? What statistics were used to determine this?

31. Were the results reasonable from the perspective of others besides the researcher him/herself? What others were involved in inspecting the results for reasonableness?

32. Do you believe the research is the best that could be conducted to reach the researchers conclusion?

33. What effect will the research conclusion have on society or the economy?

34. What would you change in the analysis to improve the analysis and support a better conclusion? (E.g. use more data observations, or better choice of independent variables, or have more conclusive analysis of algorithm or model error (residuals), etc....)

Attachment:- Assignment Files.rar