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This is exhibited by figure 3 in the appendix. Tis variable was used to measure the average cash compensation awarded to CEO for the 73 companies over the period of the last five years. Te analysis of compensation shows that Index 1 companies had a mean growth rate of 78. Wile on the other hand, Idex 2 companies had a compensation growth rate of 33.29% for their CEO’s. Idex 3 companies had a compensation growth rate of 16.34% over a period of five years (Healey, 2011). Te mean compensation rate for all the companies stood at 32.04% and Index 3 companies did not meet this set out criteria.

Terefore, w can conclude that companies with long term plans have the capability of compensating their employees in a proper manner. Tis is shown by figure 4 in the appendix (Moore, 2006). Te process of analyzing the data from the 73 small companies was done through the use of SPPS software. Uing the software, w first define the five variables used in the data in SPSS. Ater the definition of we conduct analysis by comparing the means under the statistics tab then choose compare means and choose means.

Aternatively instead of choosing means you could choose ANOVA and then analyze all the variables as it was done in this assignment. Uing SPSS ensures accuracy of the analysis being undertaken. Oher tests that can be conducted under the SPSS statistics tab are One-sample T Test, Idependent-Samples T Test, Pired-Samples T Test and One-Way ANOVA (Johnson, 2009). Te outputs of these results are the ones used in the analysis of data it was done above in this assignment.

I the process of analyzing data, sveral procedures have to be utilized in a proper and structured manner. Fom the analysis of statistics using the t-test, w get a mean value of 33. Te upper confidence levels stood at 42.19% while the lower levels of confidence stood at 24. Te ANOVA analysis of all the variables compared to the index variable show the significance of the entire analysis exhibit a figure of between 2.82 and 19. Te significance of the results show the ranges of figures are quite related.

Te income variable gives us the best results in terms of its significance to the study being undertaken. Fr instance, te significance of the income figure is 0.067 and this resonates well with the results of the analysis. AOVA analysis show that results of...

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