¶ … Mann-Whitney U Test
The mean length of stay will be equal to 14 days.
The hypothesis is rejected. Based on the one-sample t-test, the mean length of stay in this sample is not 14, nor does 14 days fall within the range of the 95% confidence intervals.
A Mann-Whitney U test was conducted using gender as a nominal grouping variable. The results indicate that there is not a significant difference in the length of stay based on gender (p. 229).
Kruskal-Wallis H Test
A One-Way ANOVA was conducted using Age (3 levels) and number of cardiac risk factors. No significant difference was found between the three age groups in the number of cardiac risk factors.
The median number of risk factors will differ based on age group.
The hypothesis is rejected. The results of the Kruskal-Wallis Test indicate that there is no significant difference between the median number of cardiac risk factors between the various age groups, X2 (2, 84) = 2.611, p = .271.
Chi Square Test
Hypothesis: The proportion of men and women alive at discharge will be the same.
They hypothesis is rejected. The Chi-Square was significant X2 (1, 84) = 4.403, p < .05. The proportion of females alive at discharge was much greater than the proportion of males alive at discharge. This can be seen in the barchart below.
alive discharge * gender Crosstabulation
gender
Total
male female alive discharge no
Count
7
5
12
Expected Count
3.9
8.1
12.0
yes
Count
20
52
72
Expected Count
23.1
48.9
72.0
Total
Count
27
57
84
Expected Count
27.0
57.0
84.0
4) Correlation & Regression
Variables: Hours in Operating Room & Number of Preop Risk Factors
Scatter Plot:
Hypothesis: The population correlation coefficient is equal to 0.
The hypothesis fails to be rejected. The correlation coefficient is not significant (p. = .694).
The value of R. was .043 and the R. Squared value was .002, which, had the model been significant, would have indicated that the number of pre-op risk factors accounted for .02% of the variability in hours spent in the operating room.
In the sample examined, the number of pre-op risk factors is not related to the hours spent in the operating room.
References
Norusis, M.J. (2008). Guide to Data Analysis. SPSS Statistics 17.0.
