T-test, One-Way ANOVA, Two-Way ANOVA and Hypotheses Testing

SPSS Analysis
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SPSS Analysis
1) SPSS hypothesis testing
a)
Ho: Average monthly earnings before covid19 crisis of service industry workers were above $3,000
Ha: Average monthly earnings before covid19 were not above $3,000
The variables being compared are earnings pre-covid19 and $3,000. The dependent variable is pre-covid19, while the independent variable is $3,000. Earnings pre-covid19 is an ordinal scale type of variable. The confidence level is 0.05. The samples for this analysis are paired.
Normality test
The significant level of Shapiro-Wilk is 0.000, which is lower than 0.05. It means that the data is statistically significant; therefore, reject the null hypothesis. Consequently, the information is not normally distributed.
Interpretation and reporting results
The sample size is 414 cases. The mean of earnings before covid19 is 31000.6836, which is higher than $3000
The significance level is 0.321, which is higher than 0.05; therefore, we fail to reject the null hypothesis that average monthly earnings before the covid19 crisis of service industry workers were above $3,000.
Therefore, the test shows 95% assurance that earnings before covid19 were above $3000.
b)
Ho: Average monthly earnings before Covid19 crisis of service industry workers were higher than average monthly earnings after Covid19 crisis
Hi: Average monthly earnings before the Covid19 crisis of service industry workers were not higher than average monthly earnings after the Covid19 problem.
The variables being compared are earnings pre-covid19, and earnings post Covid19 which are all independent variables. Earnings pre-covid19 and earnings post-covid19 are ordinal scale types of variables. The confidence level is 0.05. The samples are Independent.
Normality test.
The significant level of Shapiro-Wilk for both earnings pre-Covid19 and post-Covid19 is 0.000, which is lower than 0.05. Consequently, the information is not normally distributed for both earnings. It means that the data is statistically significant; therefore, reject the null hypothesis.
Interpretation and reporting results
The means show that salaries reduced to $1788. 06 from $3100.68 post covid19.
The significance level is 0.000 for both variables, lower than 0.05; therefore, we reject the null hypothesis that service industry workers' average monthly earnings before the Covid19 crisis were higher than average monthly earnings after the Covid19 problem.
Therefore, the test shows that 95% of service industry workers' average monthly earnings before the Covid19 crisis were not higher than average monthly earnings after the Covid19 problem.
C)
Ho: The service industry workers that are paid annual salary had a more significant reduction in earnings than those that were on an hourly wage
Hi: The service industry workers paid annual salary had no more significant reduction in earnings than those on an hourly wage.
The variables being compared are earnings percentage and hourly wages, which are all independent variables. Earnings pre-covid19 and earnings post-covid19 are ordinal scale types of variables. The confidence level is 0.05. The samples are Independent.
Normality test
The significant level of Shapiro-Wilk for both earnings percentage and hourly wages is 0.000, which is lower than 0.05. Consequently, the information is not normally distributed for both earnings. It means that the data is statistically significant; therefore, reject the null hypothesis.
Interpretation and reporting results
The mean shows that salaried employees have a more significant mean of 48.75 than hourly wage employees, who had a standard of 16.48.
The significance level is 0.00 for paired variables that are lower than 0.05; therefore, reject the null hypothesis that the service industry workers paid annual salary had a more significant reduction in earnings than those on an hourly wage.
Therefore is true to say that the test shows 95% of that the service industry workers that are paid annual salary had no more significant reduction in earnings than those that were on an hourly wage.
d)
Ho: More service industry workers are paid wedges than salary
Ha: More service industry workers are not paid wedges than salary
The variable is employment type which is an independent and nominal kind of variable. The confidence level is 0.05. The samples are Independent.
Normality test
The significant level of Shapiro-Wilk for both earnings percentage and hourly wages is 0.000, which is lower than 0.05. Thus the information is not normally distributed for both earnings. It means that the data is statistically significant; therefore, reject the null hypothesis.
Interpretation and results
The frequency shows that annual salary employees have been less compensated than hourly wage employees.
Therefore we fail to reject the null hypothesis more service industry workers are paid wedges than salary.
e) Ho: Service Industry workers paid an annual salary are less likely to be on unpaid leave than those on an hourly wage.
Ha: Service Industry workers who are paid an annual salary are more likely to be on unpaid leave than those on an hourly wage.
The variable is employment status which is an independent and nominal type of variable. The confidence level is 0.05. The samples are Independent.
Normality test
The significant level of Shapiro-Wilk for both earnings percentage and hourly wages is 0.000, which is lower than 0.05. Thus the information is not normally distributed for both earnings. It means that the data is statistically significant; therefore, reject the null hypothesis.
Interpretation and results
The frequency data shows that more employees don't get paid on leave.
Therefore, we reject the null hypothesis that service Industry workers paid an annual salary are less likely to be on unpaid leave than those on an hourly wage.
2) One way ANOVA
The research question is;
Do customers who travel for different reasons such as business, leisure, and mixed have further customer satisfaction with hotel rooms?
Hypothesis;
HO; Business travelers have the same satisfaction as leisure tr...