BA 3300 Example 2 Hospital LOS
1) Can we conclude with 95% confidence that the average hospital Length
of stay (LOS) is reduced from 5.0 days following administrative changes
data for a relatively large (>30) sample of 100 recent patients is provided
1) Data conversion
Data is provided as ASCII files. import the data into EXCEL
2) Generate descriptive statistics (with 90% CL)
Why would you use a 90% CL in the descriptive statistics procedure
even though you want to test at the 95% level
3) Generate a histogram for the LOS data
Make a histogram of the hospital LOS data. (doing this for the small pollution
sample might be a little ridiculous)
Does it look like a normal distribution?
Why is it okay to use statistical tests that assume bell-shaped (t and
z distributions) curves?
4) Use a t test to test the hypotheses:
State null and Alternative (that's what the "A" stands
for in Ha) Use Alpha=0.05 for all these tests, Hypothesized difference
Is it okay to use t instead of Z for the LOS case even though the sample
is large? why or why not?
use excel to generate appropriate P values for the observed T's. What do
these mean? What do you conclude?
Refer to the descriptive statistics, the histograms, and the P values.
Why do we use standard error instead of standard deviation in calculation
of t values?
What do the "critical t values" mean?
What are your conclusions?
What are at least three things you could do to improve ability to detect
differences between the hypothesized values and reality?