Final Submission of Final Project Part II: Statistical Report
lrodrigugz0z09
Dataanalysis.docxRunning head: Final Project Data Analysis 1
Final Project Data Analysis 2
Final Project Data Analysis:
Luz Rodriguez
Southern New Hampshire University
Process and calculations
In completing the research on the influence that gender (male/female) has over the length of the hospital stay. We can use several types of statistical tests in analysis a more accurate analysis of the research question. This involves a dot plot and a histogram. In responding to this question, we can place gender in one category but studying it under two separate samples, male and female and the effects of length of stay after a myocardial infarction. We can compute this by resolving quantitative data and the relationship between the two factors s dot plot and a histogram would be effective in achieving this analysis.
|
Research question |
To what extent does gender influence length of hospital stay for MI patients? |
|
Response and predictor variables |
Response: Length of hospital stay (LOS) -Predictor: Gender (female and male)
|
|
Type of variable for predictor variable |
Predictor: gender (female or male) |
|
Type of diagram for analysis |
Dot plot Histogram |
|
|
|
Data analysis
As shown the data tries to compare the differences between gender (male and Female) and the length of stay in hospitals with respect to each other. It’s clear that the length of hospital stay which is represented by 0 is shorter as compared to that of the female which is represented by 1. If there is a larger differences between the two genders, then there is a meaning which would reduce the standard deviation (Gerstman, 2015).
|
gender |
n |
mean |
variance |
Std. dev |
Std. err. |
median |
range |
min |
max |
Q1 |
Q3 |
|
0 |
65 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
|
1 |
35 |
1 |
0 |
0 |
0 |
1 |
0 |
1 |
1 |
1 |
1 |
Hypothesis test results:
|
Difference |
Sample Diff. |
Std. Err. |
DF |
T-Stat |
P-value |
|
μ1 - μ2 |
6.49 |
0.59375453 |
198 |
10.930443 |
<0.0001 |
References
Gerstman, B. B. (2015). Basic Biostatistics Statistics for Public Health (2nd ed.). Burlington, MA: Jones & Bartlett Learning.
gender 1 0.0 10.0 20.0 30.0 40.0 50.0 60.0 30.0 4.0 0.0 0.0 0.0 0.0 1.0
gender 0 2.0 17.0 34.0 3.0 6.0 1.0 3.0 gender 1 30.0 4.0 0.0 0.0 0.0 0.0 1.0
gender 0 0.0 2.5 5.0 7.5 10.0 12.5 15.0 2.0 17.0 34.0 3.0 6.0 1.0 3.0
