In this question you are using the data set HATCO which is under Additional Resources on myunisa on the folder called Data Sets. Use SPSS to answer the following questions. (a) Is the data appropriate for factor analysis? Substantiate your answer. (5) (b) Which variables will be appropriate for factor analysis? (7) (c) Include factor analysis using the principal component analysis with a promax rotation. Ensure that you include the scree plot, and under options sort the factors by size and use items with factor loadings .5 and above. Just produce the output and include all of it in your assignment. (20) (d) How many factors will be needed if the criterion is to explain 80% of the total variance? (2) (e) What do you notice about the item "Price flexibility"? (2) (f) Create new variable "Price flexibility2" by computing the necessary transformation of "10 - Price flexibility" and recreate factor analysis using the principal component analysis with a promax rotation using "Price flexibility2" instead of "Price flexibility". Just produce the output and include all of it in your assignment. Do not suppress small coefficients in your output.(25) 4 HRSTA82/011/0/2021 (g) Interpret the results of the factor analysis (including appropriateness of the factor analysis, grouping the variables according to the factor loadings and suggesting, with justification, possible labels for the factors). (25) (h) Show numerically that the communality estimate for Price flexibility2 is :714. Interpret this estimate. (7) (i) Do reliability analysis of the factors obtained in (f) and give the reliability coefficient for each construct and the overall reliability analysis of the instrument, and interpret it using Jain and Angural (2017) guidelines. (20) (j) Three new variables were created, using the factor analysis. (i) Explain how these new variables for each respondent may be obtained. (3) (ii) Suggest one possible way that these new variables can be used (3) (k) Discuss the rotation method used, paying specific attention to: (i) the method used, its implications and appropriateness, (4) (ii) the necessity of the rotation method, and (3) (iii) the success of the rotation method. (3) (l) Calculate the composite variables of each factor (by taking the average), and give the descriptive statistics for the composite variables and interpret them. (30) (m) Use the distribution command in SAS JMP to test for normality of the three composite variables created. (Hint: Use histograms, boxplots, normal quantile plots and Shapiro Wilk's test). Ensure that on the summary statistics output you add skewness and kurtosis on your analysis results. (15) (n) Do bivariate profiling of all variables by drawing box plots for all the variables by X8 D Size of firm, X11 D Specification buying, X12 D Structure of procurement, X13 D Type of industry and X14 D Type of buying situation. (Hint: Hair et. al., 2019:54 Figure 2-3) and comment on your plots. (75) (o) For each of the composite variable compute zskeweness D skewness q 6 N and zkurtosis D kurtosis q 24 N and hence tests for normality. (15) 5 (p) The results in (m) and (o) agree? Explain for each composite variable. (6) (q) For those variables that are nonnormal if any, determine the transformation that makes them more nearly normal. (5) (r) Test whether the mean of the composite variables differs by: (i) X8 D Size of firm. (45) (ii) X11 D Specification buying. (45) (iii) X12 D Structure of procurement. (45) (iv) X13 D Type of industry. (45) (v) X14 D Type of buying situation. (45) (Ensure that you draw error bars, and for variables with more than two categories you do posthoc analysis)