Effect of Employee Job Satisfaction on Organization Performance in Hotel Industry

Running head: Statistics 1
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Statistics 2
Part A
The research by Deshpande, Arekar, Sharma, and Somaiya (2012) was aimed at examining
the effect of employee job satisfaction on the performance of an organization with a specific
focus on the hotel industry. The statistical analysis approaches used include ANOVA (F-test),
Chi-square test, and t-test. The three statistical analysis methods were chosen because of the
multiple differences in the variables under study. For instance, a Chi-square test was to be
undertaken in instances where the data types of both variables were nominal. Analysis of
variance (ANOVA) was to be used in situations where only a single data set was nominal and
the other one is of a ratio in nature i.e. more than two categories exist. Moreover, an
independent t-test was to be carried out if one data set was ratio or interval (on condition that
only two categories exist) in nature and the other one nominal. Additionally, the overall
satisfaction levels were measured using the mean and median values.
The Bartlett’s test of sphericity was used to ascertain the strength of the association between
the study variables by making use of an approximate Chi-square value. More specifically, the
approach was used to test the null hypothesis that there was no correlation in the study
variables.
The analysis of variance was used to test the difference in the means of the six computed
variables for job satisfaction which includes role clarity, financial benefits, work stress, work
environment, workers relations and welfare. An F-test was used to compare equality of two
different variances. The decision to reject or accept the null hypothesis was based on the
computed and statistic value of F. If the computed F value was larger than the F statistic, then
the null hypothesis was rejected and vice versa. More specifically, ANOVA was used to test
the association between experience, salary, and department with job satisfaction.