Description
I completed the data work requested for exercise #1. Could you please verify I did this correctly? If so, I dont understand the difference in standard deviation and the p-value. I have to answer which year was better for the hospitals and why, but I don’t understand what I’m looking at. Attached is the raw data sheet, my work for each subject and my final answers on the word document. Remember, this is only for exercise #1, even though there are other exercises present.
Unformatted Attachment Preview
University of Maryland Global College (Updated: 7/6/2020)
HMGT 400 Research and Data Analysis in Health Care-Exercise
Dataset: HMGTHOSP.csv (Please download dataset from the class).
Required program: RStudio or R Programming.
Author, Hossein Zare, PhD
Citation: Zare, H. (2017). HMGT 400 7980 Research and Data Analysis in Health Care-Exercise. UMGC.EDU
For each week exercise, For the RStudio codes and a video, please follow the class announcement page.
Exercise #1:
The attached dataset provides some information about hospitals in 2011 and 2012. Download the data, analyze it,
then complete the descriptive table below. Please use the following format to report your findings.
Table 1. Descriptive statistics between hospitals in 2011 & 2012
2011
2012
Hospital Characteristics
N
Mean
St. Dev N
Mean
St. Dev
1. Hospital Beds
1505
377
561
1525
377
580
2. Number of paid Employees
1498
1237
1615
1515
1491
1961
3. Number of non-paid Employees
30
40
73
30
45
81
4. Total Hospital Cost ($)
1505
1525
216873322
304570722
214748023
294143536
5. Total Hospital Revenues ($)
1505
1525
228706319
323339811
229978391
321273114
6. Available Medicare Days
1499
16739
19214
1516
17110
19766
7. Available Medicaid Days
1484
5301
9208
1501
5366
9340
8. Total Hospital Discharges
1500
9492
10899
1517
9544
10994
9. Total Medicare Discharges
1499
3231
3389
1516
3598
3786
10. Total Medicaid Discharges
1481
1131
1757
1498
1120
1740
Round mean and st.dev figures to nearest whole number. Use 2 decimal places for p values.
p-value
0.99
0.00
0.81
0.85
0.91
0.60
0.85
0.90
0.01
0.86
Based on your findings, in which year did hospitals have better performance? Please write a short paragraph
describing your findings. Make sure to attach any plotted information.
(Note: Master RStudio script is available for this exercise, but you may need to modify that for this analysis)
HMGT 400 Research and Data Analysis in Health Care-Exercise, page 1
Exercise #2:
Using the dataset from week 1 exercise, answer the following questions.
Compare the following information between teaching and non-teaching hospitals using a t-test:
1) What are the main significant differences between teaching and non-teaching hospitals? (use t-test)
2) Comparing hospital net-benefit, which hospitals had better performance? (To answer this question,
first compute the hospital net benefits by subtracting hospital costs from revenues, then use a ttest to compare the significant differences between teaching and non-teaching hospitals).
3) Use a box-plot to compare hospital-cost and hospital-revenues between teaching and non-teaching
hospitals. Make sure to attach the plotted information.
4) Write a short paragraph describing your findings highlighting their importance for managerial
decision-making. List a specific managerial function and the way the processed data can be used to
meet the managerial objectives.
Table 2. Descriptive statistics between teaching and non-teaching hospitals, 2011 & 2012
Teaching
Non-Teaching
Hospital Characteristics
N
Mean
St. Dev N
Mean
St. Dev
1. Hospital Beds
2. Number of paid Employees
3. Number of non-paid Employees
4. Interns and Residents
5. System Membership
6. Total Hospital Cost ($)
7. Total Hospital Revenues ($)
8. Hospital Net Benefit ($)
9. Available Medicare Days
10. Available Medicaid Days
11. Total Hospital Discharges
12. Total Medicare Discharges
13. Total Medicaid Discharges
Round mean and st.dev figures to nearest whole number. Use 2 decimal places for p values.
p-value
(Note: Master RStudio script is available for this exercise, but you may need to modify that for this analysis)
HMGT 400 Research and Data Analysis in Health Care-Exercise, page 2
Exercise #3:
The dataset provides Herfindahl–Hirschman Index and herfindahl index categories, please use the herf_cat variable
to answer the following questions:
Note: “The Herfindahl–Hirschman Index is a commonly accepted measure of market concentration used by antitrust
enforcement agencies and scholars in the field. The HHI is calculated by squaring the market share of each firm
competing in the market and then summing the resulting numbers” (NASI, 2015; pp: 14-16). Read more from here:
https://www.urban.org/sites/default/files/publication/50116/2000212-Addressing-Pricing-Power-in-Health-CareMarkets.pdf
For this exercise you do not need to compute the HHI, but if you have any questions, please do not hesitate to ask.
However, try to learn more about this you will need that to report your findings.
Using the dataset from week 1 exercise, answer the following questions.
Comparing the following information between hospitals located in high, moderate and low competitive markets
below. (Table 3)
1) What are the main significant differences between hospitals in different markets? (use Anova test)
2) Using density curves or boxplots, compare hospital cost and revenues across the three markets.
3) What is the impact of being in a high-competitive market on hospital revenues and cost? Do you think
being in a high-competitive market has a positive impact on hospital net benefits? What about the
number of Medicare and Medicaid discharges? Do you think hospitals in high-competitive market are
more likely to accept more Medicare and Medicaid patients? What is the impact of other variables?
Please discuss your findings in 1-2 paragraphs.
(Note: To answer the last question, compute the Medicare-discharge and Medicaid-discharge ratios
first, then run 2 t-tests: high vs. moderate, and high vs. low competitive market). Please support your
findings with box-plots. [Medicare and Medicaid Discharge Ratios: Total Medicare Discharges ÷ Total
Hospital Discharges; Total Medicaid Discharges ÷ Total Hospital Discharges]
Table 3. Comparing hospital characteristics and market, 2011 and 2012
High Competitive
Market
Hospital Characteristics
N
Mean
St.
Dev
Moderate
Competitive
Market
N
Mean
St.
Dev
Low Competitive
Market
N
Mean
St.
Dev
ANOVA
/Chi-Sq
(results)
P value
1. Hospital Beds
2. Number of paid Employees
3. Number of non-paid Employees
4. Interns and Residents
5. System Membership
6. Total Hospital Cost ($)
7. Total Hospital Revenues ($)
8. Hospital Net Benefit ($)
9. Available Medicare Days
10. Available Medicaid Days
11. Total Hospital Discharges
12. Total Medicare Discharges
13. Total Medicaid Discharges
14. Medicare Discharge Ratio
15. Medicaid Discharge Ratio
14. Herfindahl Index
Round mean and st.dev figures to nearest whole number (except Herfindahl index). Use 2 decimal places for p values.
(Note: Master RStudio script is available for this exercise, but you may need to modify that for this analysis)
HMGT 400 Research and Data Analysis in Health Care-Exercise, page 3
Exercise #4
Linear Regression Model
If you have chosen to work with RStudio, please run the following linear regression model and complete the
following tables using dataset from week 1’s exercise.
Medicare and Medicaid Discharge Ratios: Medicare Discharges ÷ Total Hospital Discharges; Medicaid Discharges ÷ Total
Hospital Discharges
1st Model:
Run a linear model to predict the impact of number of hospital beds (use the bed-tot) and hospitals ownership on hospital net-ben
efit. Discuss your finding. Do you think having higher number of beds has a positive impact on the hospital net benefit? What ab
out the ownership?
Hospital Characteristics
Hospital beds
Ownership
For-Profit
Not-for-profit
Other
N
R-Squared
Coef.
St. Err
P value
(Limit all results to 2 decimal places max)
2nd Model:
Now, estimate the impact of being a member of a system on hospital net benefit. Discuss your finding (not more than 2 lines)? Is
it significant?
Hospital Characteristics
Hospital beds
Ownership
For-Profit
Not-for-profit
Other
Membership
System Membership
N
R-Squared
Coef.
St. Err
P value
(Limit all results to 2 decimal places max)
3rd Model:
Now, include the Medicare and Medicaid discharge ratios in your model. How do you evaluate the impact of having
higher Medicare and Medicaid patients on hospital revenues?
Hospital Characteristics
Hospital beds
Ownership
For-Profit
Not-for-profit
Other
Membership
System Membership
Socio-Economic Characteristics
Medicare discharge ratio
Medicaid discharge ratio
N
R-Squared
Coef.
St. Err
P value
(Limit all results to 2 decimal places max)
Based on your findings, recommend 3 policies to improve hospital performance. Please make sure to use the final
model for your recommendations.
HMGT 400 Research and Data Analysis in Health Care-Exercise, page 4
If you have chosen to work with Excel, please run the three linear regression models and complete the following
tables using the dataset from week 1’s exercise.
Medicare and Medicaid Discharge Ratios: Medicare Discharges ÷ Total Hospital Discharges; Medicaid Discharges ÷ Total
Hospital Discharges
Model 1:
Run a linear model to predict the impact of number of hospital beds (use bed-tot) on hospital net-benefit in teaching
hospitals.
Hospital Characteristics
Hospital beds
R Squared
Coef.
ST. ERR
T Stat
P-values
Lower 95%
Upper 95%
(Limit all results to 2 decimal places max)
Model 2:
Run a linear model to predict the impact of number of hospital beds (use bed-tot) on hospital net-benefit in non-teac
hing hospitals.
Hospital Characteristics
Hospital beds
R Squared
Coef.
ST. ERR
T Stat
P-values
Lower 95%
Upper 95%
(Limit all results to 2 decimal places max)
Use the results from model 1 and model 2 and compare the results between teaching and non-teaching hospitals.
Model 3:
Now, include the Medicare and Medicaid discharge ratios in first model. How do you evaluate the impact of having
higher Medicare and Medicaid patients on hospital net-benefit in teaching hospitals?
Hospital Characteristics
Hospital beds
Medicare-discharge-ratio
Medicaid-discharge-ratio
R Squared
Coef.
ST. ERR
T Stat
P-values
Lower 95%
Upper 95%
(Limit all results to 2 decimal places max)
Model 4:
Now, include the Medicare and Medicaid discharge ratios in first model. How do you evaluate the impact of having
higher Medicare and Medicaid patients on hospital net-benefit in non-teaching hospitals?
Hospital Characteristics
Hospital beds
Medicare-discharge-ratio
Medicaid-discharge-ratio
R Squared
Coef.
ST. ERR
T Stat
P-values
Lower 95%
Upper 95%
(Limit all results to 2 decimal places max)
Based on your findings, recommend 3 policies to improve hospital performance. Please make sure to use the final
model for your recommendations.
HMGT 400 Research and Data Analysis in Health Care-Exercise, page 5
Exercise #5
For this week’s exercise, we need to try a few logit (logistic regression) models (see this link for more information:
https://stats.idre.ucla.edu/r/dae/logit-regression/). Use same dataset from week 1 exercise.
Medicare and Medicaid Discharge Ratios: Medicare Discharges ÷ Total Hospital Discharges; Medicaid Discharges ÷ Total
Hospital Discharges
If you have chosen to work with RStudio, please run the following linear regression model and complete the
following tables using dataset from week 1 exercise.
Model 1
Run a logit model using being a member of network as the outcome/dependent variable and find its impact on
hospital ownership and hospital beds.
Hospital Characteristics
Hospital beds
Ownership
For-Profit
Not-for-profit
Other
N
AIC
Coef.
St. Err
p-value
(Limit all results to 2 decimal places max)
Model 2
Now, include hospital net benefits and report the Coeff.
Hospital Characteristics
Hospital beds
Ownership
For-Profit
Not-for-profit
Other
Hospital net benefits
N
AIC
Coef.
St. Err
p-value
(Limit all results to 2 decimal places max)
Model 3
Now, include the Medicare and Medicaid discharge ratios in your model. Do you recommend keeping membership for
a hospital? Why or why not?
Hospital Characteristics
Hospital beds
Ownership
For-Profit
Not-for-profit
Other
Hospital net benefits
Medicare discharge ratio
Medicaid discharge ratio
N
AIC
Coef.
St. Err
p-value
(Limit all results to 2 decimal places max)
Based on your findings, recommend 3 policies to improve hospital performance in For-Profit and Not-For-Profit
hospitals. Please make sure to use the final model for your recommendations.
HMGT 400 Research and Data Analysis in Health Care-Exercise, page 6
If you have chosen to work with Excel, please run below three models and complete the following tables. Use same
dataset from week 1’s exercise.
Medicare and Medicaid Discharge Ratios: Medicare Discharges ÷ Total Hospital Discharges; Medicaid Discharges ÷ Total
Hospital Discharges
Model 1: Run a regression model using being a member of a network and find out its impact on hospital cost.
Coef.
ST. ERR
Wald
Stat
P-values
Lower 95%
Upper 95%
Hospital cost
N
R Squared
(Limit all results to 2 decimal places max)
Model 2: Run a regression model using being a member of a network and find out its impact on hospital cost and
hospital revenue.
Coef.
ST. ERR
Wald
Stat
P-values
Lower 95%
Upper 95%
Hospital cost
Hospital Revenue
N
R Squared
(Limit all results to 2 decimal places max)
Model 3: Run a regression model using being a member of a network and find out its impact on Medicare and
Medicaid discharge ratios.
Coef.
ST. ERR
Wald
Stat
P-values
Lower 95%
Upper 95%
Hospital cost
Hospital Revenue
Medicare discharge ratio
Medicaid discharge ratio
N
R Squared
(Limit all results to 2 decimal places max)
Based on your findings, recommend 3 policies and discuss the impact of being a member of a network on hospital
cost, hospital revenue as well as Medicare and Medicaid discharge ratios. Do you recommend keeping membership
for a hospital? Why or why not?
HMGT 400 Research and Data Analysis in Health Care-Exercise, page 7
Variable Name
state_name
stcd
year
total_hosp_cost
total_hosp_revenue
total_hospital_benefits
hospital_beds
bedsize_cat
teaching_hospital
system_member
level_trauma
white
rural_area
Variable
Description
State Name
State Code
Variable Type
Categorical
Categorical
Categorical
2011
Total Hospital Cost Continuous
Total Hospital
Revenue
Total Hospital
Benefits
Number Hospital
Beds
Hospital Bed Size
Category
Hospital Type or
Status
Continuous
Continuous
Continuous
Categorical
Categorical
System Membership
or Member of a
Categorical
Network
Trauma Level
Percent White
Population
0=No
Continuous
Herfindahl Index
Categorical
Category
Herfindahl Index
herf_index
Continuous
Category
Percent Non-white
non_white
Continuous
population
Log of Hospital
log_hosp_cost
Cost
Log of Hospital
log_hosp_revenue
Revenue
Total Number
total_hospital_beds
Continuous
Hospital Beds
total_hospital_medicare_d Number Medicare
Continuous
ays
Days
total_hospital_medicaid_d Number Medicaid
Continuous
ays
Days
Number Interns and
interns_and_residents
Continuous
Residents
total_hospital_employees Number Employees
Continuous
_on_payr
on Payroll
Number Non paid
Workers
0=Non Teaching
Categorical
herf_cat
total_hospital_non_paid_
workers
Categories
Continuous
0=High Competitive
total_hospital_medicare_d Number Medicare
ischarg
Discharges
Continuous
total_hospital_medicaid_d Number Medicaid
ischarg
Discharges
Continuous
total_hospital_discharges
Total Number
Continuous
Hospital Discharges
own
Ownership Type
medicare discharge ratio
Categorical
Continuous
0=Not-For-Profit
2012
1=Teaching
1=Yes
1=Moderate
Competitive
2=Low
Competitive
1=For-Profit
2=Public
3=Other
stata_namestcd
Arizona
Arizona
Arizona
Arizona
Arizona
Arizona
Arizona
Arizona
Arizona
Arizona
Arizona
Arizona
Arizona
Arizona
Arizona
Arizona
Arizona
Arizona
Arizona
Arizona
Arizona
Arizona
Arizona
Arizona
Arizona
Arizona
Arizona
Arizona
Arizona
Arizona
Arizona
Arkansas
Arkansas
Arkansas
Arkansas
Arkansas
Arkansas
Arkansas
Arkansas
Arkansas
Arkansas
Arkansas
Arkansas
Arkansas
Arkansas
Arkansas
year
86
86
86
86
86
86
86
86
86
86
86
86
86
86
86
86
86
86
86
86
86
86
86
86
86
86
86
86
86
86
86
71
71
71
71
71
71
71
71
71
71
71
71
71
71
71
total_hosp_cost
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
total_hosp_revenue
286000000.00
20000000.00
268000000.00
133000000.00
205000000.00
12700000.00
15900000.00
51500000.00
621000000.00
59000000.00
104000000.00
21400000.00
315000000.00
752000000.00
24300000.00
230000000.00
167000000.00
277000000.00
856000000.00
61200000.00
416000000.00
152000000.00
98700000.00
142000000.00
204000000.00
52200000.00
16900000.00
198000000.00
90400000.00
158000000.00
242000000.00
190000000.00
21700000.00
9958705.00
21700000.00
221000000.00
177000000.00
9470889.00
140000000.00
6956698.00
10000000.00
63700000.00
189000000.00
156000000.00
15900000.00
362000000.00
315000000.00
23800000.00
227000000.00
135000000.00
154000000.00
10700000.00
17200000.00
38000000.00
662000000.00
73800000.00
129000000.00
21900000.00
364000000.00
759000000.00
20900000.00
247000000.00
167000000.00
289000000.00
915000000.00
52600000.00
428000000.00
167000000.00
108000000.00
150000000.00
244000000.00
55600000.00
15600000.00
213000000.00
94100000.00
157000000.00
264000000.00
192000000.00
22900000.00
7292673.00
21300000.00
213000000.00
189000000.00
7856094.00
149000000.00
6222175.00
9806737.00
63700000.00
199000000.00
160000000.00
17700000.00
370000000.00
Arkansas
Arkansas
Arkansas
Arkansas
Arkansas
Arkansas
Arkansas
Arkansas
Arkansas
Arkansas
Arkansas
Arkansas
Arkansas
Arkansas
Arkansas
Arkansas
Arkansas
Arkansas
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
71
71
71
71
71
71
71
71
71
71
71
71
71
71
71
71
71
71
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
14000000.00
7307238.00
8824289.00
7340959.00
222000000.00
150000000.00
34700000.00
63800000.00
10600000.00
61100000.00
18500000.00
173000000.00
12200000.00
17400000.00
140000000.00
68700000.00
479000000.00
15200000.00
204000000.00
305000000.00
2610000000.00
408000000.00
233000000.00
227000000.00
287000000.00
437000000.00
483000000.00
68700000.00
90900000.00
95600000.00
168000000.00
74500000.00
462000000.00
268000000.00
263000000.00
639000000.00
846000000.00
362000000.00
181000000.00
455000000.00
345000000.00
390000000.00
199000000.00
306000000.00
306000000.00
305000000.00
406000000.00
13800000.00
9097677.00
8573674.00
7132202.00
229000000.00
153000000.00
35800000.00
67000000.00
9925368.00
57800000.00
19800000.00
181000000.00
13000000.00
17100000.00
155000000.00
73900000.00
496000000.00
17700000.00
185000000.00
304000000.00
2750000000.00
429000000.00
231000000.00
234000000.00
287000000.00
475000000.00
448000000.00
67900000.00
101000000.00
96100000.00
171000000.00
95900000.00
495000000.00
291000000.00
259000000.00
653000000.00
842000000.00
442000000.00
191000000.00
516000000.00
349000000.00
420000000.00
205000000.00
315000000.00
278000000.00
304000000.00
415000000.00
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
297000000.00
488000000.00
230000000.00
61700000.00
183000000.00
741000000.00
50000000.00
236000000.00
554000000.00
436000000.00
64200000.00
118000000.00
44400000.00
153000000.00
209000000.00
259000000.00
77900000.00
97000000.00
21700000.00
87100000.00
251000000.00
2070000000.00
67800000.00
271000000.00
56600000.00
90700000.00
330000000.00
40100000.00
522000000.00
268000000.00
228000000.00
48500000.00
66800000.00
573000000.00
158000000.00
343000000.00
1170000000.00
231000000.00
164000000.00
435000000.00
134000000.00
164000000.00
45800000.00
108000000.00
158000000.00
249000000.00
322000000.00
285000000.00
505000000.00
250000000.00
58700000.00
193000000.00
810000000.00
54900000.00
233000000.00
823000000.00
459000000.00
66500000.00
122000000.00
50300000.00
146000000.00
211000000.00
244000000.00
82700000.00
97200000.00
24600000.00
96600000.00
292000000.00
2260000000.00
65000000.00
291000000.00
66300000.00
116000000.00
372000000.00
45900000.00
546000000.00
284000000.00
230000000.00
45800000.00
77500000.00
601000000.00
166000000.00
350000000.00
1200000000.00
238000000.00
171000000.00
490000000.00
140000000.00
135000000.00
64400000.00
142000000.00
153000000.00
266000000.00
336000000.00
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
93
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
424000000.00
12900000.00
87200000.00
209000000.00
461000000.00
390000000.00
122000000.00
249000000.00
777000000.00
92800000.00
286000000.00
69200000.00
251000000.00
366000000.00
284000000.00
393000000.00
466000000.00
343000000.00
1080000000.00
274000000.00
557000000.00
117000000.00
856000000.00
417000000.00
73400000.00
327000000.00
183000000.00
12500000.00
465000000.00
770000000.00
449000000.00
149000000.00
51500000.00
149000000.00
259000000.00
1010000000.00
256000000.00
330000000.00
170000000.00
540000000.00
17200000.00
7587601.00
285000000.00
563000000.00
511000000.00
395000000.00
225000000.00
430000000.00
14300000.00
85200000.00
209000000.00
468000000.00
415000000.00
118000000.00
280000000.00
918000000.00
92500000.00
316000000.00
69900000.00
252000000.00
384000000.00
304000000.00
463000000.00
484000000.00
396000000.00
1100000000.00
367000000.00
537000000.00
125000000.00
1020000000.00
464000000.00
63300000.00
329000000.00
217000000.00
12400000.00
531000000.00
852000000.00
507000000.00
157000000.00
58800000.00
151000000.00
241000000.00
1080000000.00
258000000.00
325000000.00
182000000.00
518000000.00
19200000.00
7759291.00
300000000.00
606000000.00
545000000.00
386000000.00
244000000.00
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
39
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
249000000.00
105000000.00
726000000.00
54800000.00
35600000.00
131000000.00
167000000.00
447000000.00
9305769.00
182000000.00
235000000.00
110000000.00
194000000.00
28100000.00
435000000.00
88000000.00
104000000.00
243000000.00
137000000.00
86700000.00
32500000.00
223000000.00
19800000.00
21800000.00
159000000.00
206000000.00
146000000.00
40700000.00
711000000.00
541000000.00
16500000.00
287000000.00
534000000.00
205000000.00
93300000.00
210000000.00
84400000.00
9905096.00
575000000.00
88100000.00
35100000.00
179000000.00
508000000.00
68700000.00
119000000.00
67900000.00
56300000.00
264000000.00
111000000.00
786000000.00
62200000.00
34800000.00
141000000.00
174000000.00
457000000.00
9440413.00
181000000.00
235000000.00
118000000.00
215000000.00
28200000.00
473000000.00
89300000.00
52400000.00
241000000.00
162000000.00
84200000.00
20400000.00
245000000.00
18800000.00
19100000.00
155000000.00
219000000.00
143000000.00
39800000.00
777000000.00
541000000.00
12500000.00
290000000.00
543000000.00
233000000.00
112000000.00
218000000.00
103000000.00
15100000.00
662000000.00
97800000.00
32200000.00
186000000.00
524000000.00
64800000.00
117000000.00
62100000.00
66000000.00
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
38
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
79800000.00
311000000.00
54100000.00
192000000.00
95000000.00
688000000.00
409000000.00
203000000.00
35500000.00
170000000.00
241000000.00
60300000.00
693000000.00
483000000.00
119000000.00
206000000.00
87400000.00
441000000.00
160000000.00
452000000.00
183000000.00
270000000.00
265000000.00
873000000.00
815000000.00
9992391.00
966000000.00
252000000.00
224000000.00
331000000.00
228000000.00
110000000.00
45700000.00
66600000.00
34400000.00
24900000.00
286000000.00
13900000.00
162000000.00
277000000.00
143000000.00
166000000.00
291000000.00
112000000.00
32400000.00
106000000.00
91600000.00
76100000.00
320000000.00
53600000.00
212000000.00
93600000.00
786000000.00
371000000.00
216000000.00
32700000.00
177000000.00
275000000.00
62600000.00
667000000.00
506000000.00
116000000.00
196000000.00
97700000.00
446000000.00
178000000.00
405000000.00
167000000.00
294000000.00
279000000.00
979000000.00
886000000.00
10600000.00
1000000000.00
242000000.00
239000000.00
331000000.00
265000000.00
102000000.00
50700000.00
61600000.00
37900000.00
26400000.00
297000000.00
15200000.00
198000000.00
300000000.00
145000000.00
166000000.00
286000000.00
112000000.00
44300000.00
109000000.00
104000000.00
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
332000000.00
314000000.00
133000000.00
92400000.00
20100000.00
38400000.00
67900000.00
317000000.00
17800000.00
150000000.00
65300000.00
18500000.00
1220000000.00
38600000.00
148000000.00
11200000.00
74700000.00
152000000.00
31800000.00
159000000.00
382000000.00
150000000.00
29200000.00
25000000.00
119000000.00
18800000.00
469000000.00
53800000.00
28200000.00
122000000.00
1400000000.00
25700000.00
42300000.00
327000000.00
430000000.00
21600000.00
589000000.00
287000000.00
109000000.00
399000000.00
74000000.00
69100000.00
24200000.00
213000000.00
118000000.00
86400000.00
264000000.00
340000000.00
333000000.00
116000000.00
96800000.00
21300000.00
37800000.00
67900000.00
421000000.00
18000000.00
145000000.00
70000000.00
19600000.00
1360000000.00
38600000.00
144000000.00
11700000.00
78300000.00
147000000.00
30000000.00
144000000.00
360000000.00
171000000.00
33500000.00
25400000.00
133000000.00
21100000.00
495000000.00
52000000.00
28200000.00
115000000.00
1450000000.00
22400000.00
48200000.00
386000000.00
437000000.00
23400000.00
683000000.00
278000000.00
108000000.00
412000000.00
75700000.00
66300000.00
25400000.00
272000000.00
0.00
100000000.00
280000000.00
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
43
42
42
42
42
42
42
42
42
42
42
42
42
42
42
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
286000000.00
120000000.00
109000000.00
45800000.00
108000000.00
165000000.00
466000000.00
85000000.00
265000000.00
82000000.00
187000000.00
24000000.00
268000000.00
113000000.00
60500000.00
181000000.00
27100000.00
19700000.00
103000000.00
396000000.00
242000000.00
21500000.00
81700000.00
589000000.00
287000000.00
38000000.00
30900000.00
183000000.00
114000000.00
181000000.00
196000000.00
79900000.00
354000000.00
86800000.00
110000000.00
314000000.00
200000000.00
27400000.00
115000000.00
189000000.00
42300000.00
261000000.00
319000000.00
195000000.00
41500000.00
137000000.00
22400000.00
284000000.00
128000000.00
105000000.00
50100000.00
113000000.00
162000000.00
469000000.00
90300000.00
283000000.00
84900000.00
204000000.00
24500000.00
280000000.00
117000000.00
71500000.00
196000000.00
28500000.00
19900000.00
120000000.00
388000000.00
261000000.00
21300000.00
83700000.00
764000000.00
331000000.00
39100000.00
23500000.00
199000000.00
114000000.00
197000000.00
201000000.00
80200000.00
388000000.00
101000000.00
111000000.00
391000000.00
215000000.00
28200000.00
118000000.00
212000000.00
53600000.00
248000000.00
297000000.00
203000000.00
50200000.00
177000000.00
26100000.00
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Iowa
Iowa
Iowa
Iowa
Iowa
Iowa
Iowa
Iowa
Iowa
Iowa
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
62
62
62
62
62
62
62
62
62
62
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
140000000.00
24900000.00
2440000000.00
32900000.00
21800000.00
114000000.00
62100000.00
281000000.00
320000000.00
23600000.00
53900000.00
365000000.00
192000000.00
452000000.00
14700000.00
1060000000.00
148000000.00
274000000.00
325000000.00
129000000.00
25300000.00
21900000.00
194000000.00
370000000.00
50500000.00
27100000.00
500000000.00
376000000.00
40100000.00
29600000.00
63800000.00
43300000.00
306000000.00
159000000.00
503000000.00
323000000.00
190000000.00
23600000.00
44000000.00
26500000.00
21000000.00
62300000.00
49000000.00
157000000.00
6087405.00
373000000.00
85100000.00
163000000.00
27100000.00
2610000000.00
31700000.00
21400000.00
130000000.00
73900000.00
288000000.00
342000000.00
25300000.00
55300000.00
406000000.00
205000000.00
485000000.00
14900000.00
1210000000.00
171000000.00
293000000.00
3000000
