MultipleRegression Analysis
Finalproject II
Thehypothesis for the variables would be as follows:

Staffed beds: the number of staffed beds decreased between 2001 and 2005
Rationale:number of beds go with a given target capacity of the hospital

Medicare: Medicaid services increased between 2001 and 2005
Rationale:this is a service provided by the hospital

Medicaid: Medicaid services increased between 2001 and 2005
Rationale:this is a service provided by the hospital

Total surgeries: The total number of surgeries increased between 2001 and 2005
Rationale:surgeries are necessary to manage a given treatment course

RN FTE: the number of RN/FTE’s increased between 2001 and 2007
Rationale:the number of employees is determined by capacity and targets of thehospital.

Occupancy: The annual occupancy rate increased between 2001 and 2005
Rationale:occupancy is a factor of the number of beds.

Ownership: ownership of the health institution has remained constant between 2001 and 2005.
Rationale:ownership is a long term factor

System membership: System membership remained constant between 2001 and 2005.
Rationale:services improve and are guaranteed for members

Rural/ urban: migrations to the neighborhood of the health center increased between 2001 and 2005.
Rationale:health care services contribute to migration of people.

Teaching affiliation: The number of those affiliated to teaching in the profession increased between 2001 and 2005
Rationale:Health care services involve training of personnel

Age 65+ : The number of those aged 65 and above increased between 2001 and 2005
Rationale:Age is a time based factor that is incessant.

Crime rate: The rate of crime increased between 2001 and 2005.
Rationale:Every institution has its own category of crimes.

Uninsured: The number of uninsured patients has increased between 2001 and 2005.
Rationale:Insurance guarantees health services.
Thetable below gives a summary report for the data
Independent variable – predictors 
Model 
Sign 
Mean 
SD 
Con. Level 
R^2 
pvalue 
Significance 
Staffed beds X_{1} 
Y = 711066X + (2.7E+07) 
+ 
217 
190.36 
95% 
0.831612 
2.6916E32 
significant 
Medicare X_{2} 
Y = 5029X + 1230988 
+ 
25092 
23417.9 
95% 
0.629534 
1.0345E18 
significant 
Medicaid X_{3} 
Y = 6541X + 58952921 
+ 
10467 
13362.2 
95% 
0.34675 
7.38E09 
significant 
Total Surgeries X_{4} 
Y = 14419X – 2058681 
+ 
8980 
9415.5 
95% 
0.836584 
8.21397E33 
significant 
RNFTE X_{5} 
Y = 389618X + 692251 
+ 
309 
371.65 
95% 
0.95169 
9.58E54 
significant 
Occupancy X_{6} 
Y = 142210734X + 6962251 
+ 
1 
1.02 
95% 
0.95169 
9.58E54 
significant 
Ownership X_{7} 
Y = (1.7E+07)X + (1.31E+8) 
– 
0 
0.401 
95% 
0.002207 
0.677080397 
Not significant 
System Membership X_{8} 
Y = 5399390X + (1.31E+8) 
– 
1 
0.482 
95% 
0.000308 
0.87643513 
Not significant 
Rural/ Urban X_{9} 
Y = (1.4E+8)X + (1.68E+8) 
– 
0 
0.459 
95% 
0.178571 
8.5004E05 
significant 
Teaching Affiliation X_{10} 
Y = (1.79E+8) + 876688338 
+ 
0 
0.418 
95% 
0.254187 
1.598E06 
significant 
Age 65+ X_{11} 
Y = 3324X + 80228678 
+ 
14.2 
18511.5 
95% 
0.171805 
0.00012 
significant 
Crime rate X_{12} 
Y = 7976X + 73346419 
+ 
6780 
5083.5 
95% 
0.074618 
0.0136107 
significant 
Uninsured X_{13} 
Y = 2562X + 82557510 
+ 
17509 
23327.55 
95% 
0.162166 
0.000194 
Significant 
Multipleregression analysis is a powerful technique used for predicting theunknown value of a variable from the known value of two or morevariables also called the predictors [ CITATION Exp09 l 1033 ]. The use of R^{2}values will give the proportion of the predictor in terms ofprobability or percentage influence on the model [ CITATION Ask09 l 1033 ]. Given Y to represent the total operating expenses of the Hospital, amultiple linear model can be developed as follows:
Y= X_{1}+X_{2}+X_{3}+X_{4………..}+X_{13}to determine the total operating costs of the Hospital[ CITATION Owe812 l 1033 ]. The total cost therefore depends on the predictors.
References
Ask.com. (2009). math/statistics. Retrieved December 6, 2014, from Ask.com website: http://www.ask.com/math/usersquaredlinearregressionanalysisb9fa8ca142003022
Explorable. (2009). Explorable psychology experiments. Retrieved December 6, 2014, from Explorable website: https://explorable.com/multipleregressionanalysis
Owens, F., & Jones, R. (1981). Statistics. London: Polytech publishers.