Question
In: Statistics and Probability
0 Bedroom Bathroom Cars SQ FT 298,000 3 2.5 0 1,566 319,900 3 2.5 0 2,000...
| 0 | Bedroom | Bathroom | Cars | SQ FT |
| 298,000 | 3 | 2.5 | 0 | 1,566 |
| 319,900 | 3 | 2.5 | 0 | 2,000 |
| 354,000 | 3 | 2 | 2 | 0 |
| 374,900 | 4 | 2.5 | 0 | 2,816 |
| 385,000 | 4 | 2 | 0 | 0 |
| 389,000 | 3 | 2.5 | 0 | 2,248 |
| 399,000 | 4 | 3 | 0 | 2,215 |
| 415,000 | 3 | 2.5 | 0 | 3,188 |
| 444,900 | 3 | 2 | 0 | 2,530 |
| 450,000 | 3 | 2 | 0 | 1,967 |
| 465,000 | 4 | 3 | 0 | 2,564 |
| 340,000 | 4 | 2.5 | 0 | 2,293 |
| 275,000 | 3 | 2.5 | 2 | 1,353 |
| 425,000 | 3 | 2 | 0 | 1,834 |
| 250,000 | 3 | 2.5 | 0 | 5,837 |
| 450,000 | 3 | 2.5 | 0 | 9,060 |
| 390,000 | 3 | 3.5 | 0 | 1,002 |
| 269,000 | 3 | 2.5 | 0 | 1,680 |
| 425,000 | 3 | 2.5 | 2 | 4,356 |
| 425,000 | 2 | 2.5 | 2 | 2,993 |
| 425,000 | 3 | 3 | 0 | 4,356 |
| 429,900 | 5 | 3.5 | 1 | 2,154 |
| 400,000 | 3 | 2.5 | 2 | 1,846 |
| 399,900 | 3 | 2 | 1 | 2,018 |
| 388,990 | 4 | 4 | 0 | 2,295 |
- Construct and interpret a correlation matrix for your data. and explain the relationship.
- Show the step wise process of determining the best regression model to predict PRICE. EXPLAIN the process as you move from the full model to your final model.
- make 3 regression models based on cars, bedroom, bath room.
- Using your final model, select values for the independent variables and predict the house’s sales price.
Solutions
Expert Solution
Construct and interpret a correlation matrix for your data. and explain the relationship.
| Price | Bedroom | Bathroom | Cars | SQ FT |
| 1 | 0.116311 | 0.069295 | -0.01194 | 0.182509 |
| 0.116311 | 1 | 0.454391 | -0.27731 | -0.16482 |
| 0.069295 | 0.454391 | 1 | -0.14388 | 0.0818 |
| -0.01194 | -0.27731 | -0.14388 | 1 | -0.15225 |
| 0.182509 | -0.16482 | 0.0818 | -0.15225 | 1 |
The correlation matrix shows that Bedroom, SQ FT and Bathroom have a good positive relationship with Price and Cars has a negative relationship with Price.
Show the step wise process of determining the best regression model to predict PRICE. EXPLAIN the process as you move from the full model to your final model.
The regression output is:
| R² | 0.060 | |||||
| Adjusted R² | 0.000 | |||||
| R | 0.245 | |||||
| Std. Error | 63973.056 | |||||
| n | 25 | |||||
| k | 4 | |||||
| Dep. Var. | Price | |||||
| ANOVA table | ||||||
| Source | SS | df | MS | F | p-value | |
| Regression | 5,22,26,51,649.4394 | 4 | 1,30,56,62,912.3598 | 0.32 | .8619 | |
| Residual | 81,85,10,38,446.5607 | 20 | 4,09,25,51,922.3280 | |||
| Total | 87,07,36,90,096.0000 | 24 | ||||
| Regression output | confidence interval | |||||
| variables | coefficients | std. error | t (df=20) | p-value | 95% lower | 95% upper |
| Intercept | 3,09,980.8034 | |||||
| Bedroom | 17,945.0381 | 25,574.4249 | 0.702 | .4910 | -35,402.2774 | 71,292.3537 |
| Bathroom | -2,595.9465 | 28,990.2834 | -0.090 | .9295 | -63,068.6180 | 57,876.7249 |
| Cars | 5,114.6350 | 16,897.8149 | 0.303 | .7653 | -30,133.5893 | 40,362.8593 |
| SQ FT | 7.3638 | 7.4722 | 0.985 | .3362 | -8.2230 | 22.9505 |
The best regression model to predict PRICE is:
PRICE = 3,09,980.8034 + 17,945.0381Bedroom -2,595.9465Bathroom + 5,114.6350Cars + 7.3638SQ FT
make 3 regression models based on cars, bedroom, bath room.
The regression models based on cars is:
| r² | 0.000 | |||||
| r | -0.012 | |||||
| Std. Error | 61524.573 | |||||
| n | 25 | |||||
| k | 1 | |||||
| Dep. Var. | Price | |||||
| ANOVA table | ||||||
| Source | SS | df | MS | F | p-value | |
| Regression | 1,24,07,863.4877 | 1 | 1,24,07,863.4877 | 0.00 | .9548 | |
| Residual | 87,06,12,82,232.5123 | 23 | 3,78,52,73,140.5440 | |||
| Total | 87,07,36,90,096.0000 | 24 | ||||
| Regression output | confidence interval | |||||
| variables | coefficients | std. error | t (df=23) | p-value | 95% lower | 95% upper |
| Intercept | 3,83,919.1626 | |||||
| Cars | -874.0887 | 15,267.0666 | -0.057 | .9548 | -32,456.4221 | 30,708.2448 |
The estimated regression equation is:
PRICE = 3,83,919.1626 -874.0887Cars
The regression models based on bedroom is:
| r² | 0.014 | |||||
| r | 0.116 | |||||
| Std. Error | 61111.349 | |||||
| n | 25 | |||||
| k | 1 | |||||
| Dep. Var. | Price | |||||
| ANOVA table | ||||||
| Source | SS | df | MS | F | p-value | |
| Regression | 1,17,79,59,510.1593 | 1 | 1,17,79,59,510.1593 | 0.32 | .5798 | |
| Residual | 85,89,57,30,585.8407 | 23 | 3,73,45,96,981.9931 | |||
| Total | 87,07,36,90,096.0000 | 24 | ||||
| Regression output | confidence interval | |||||
| variables | coefficients | std. error | t (df=23) | p-value | 95% lower | 95% upper |
| Intercept | 3,46,057.9646 | |||||
| Bedroom | 11,415.1327 | 20,325.3324 | 0.562 | .5798 | -30,631.0207 | 53,461.2862 |
The estimated regression equation is:
PRICE = 3,46,057.9646 + 11,415.1327Bedroom
The regression models based on bath room is:
| r² | 0.005 | |||||
| r | 0.069 | |||||
| Std. Error | 61381.057 | |||||
| n | 25 | |||||
| k | 1 | |||||
| Dep. Var. | Price | |||||
| ANOVA table | ||||||
| Source | SS | df | MS | F | p-value | |
| Regression | 41,81,05,299.9432 | 1 | 41,81,05,299.9432 | 0.11 | .7421 | |
| Residual | 86,65,55,84,796.0568 | 23 | 3,76,76,34,121.5677 | |||
| Total | 87,07,36,90,096.0000 | 24 | ||||
| Regression output | confidence interval | |||||
| variables | coefficients | std. error | t (df=23) | p-value | 95% lower | 95% upper |
| Intercept | 3,62,547.9653 | |||||
| Bathroom | 8,120.7886 | 24,377.5318 | 0.333 | .7421 | -42,307.9781 | 58,549.5553 |
The estimated regression equation is:
PRICE = 3,62,547.9653 + 8,120.7886Bathroom
Using your final model, select values for the independent variables and predict the house’s sales price.
Let a place has 3 Bedroom, 2 Bathroom, 8 Cars and an area of 3,000 SQ FT.
The house’s sales PRICE will be:
The best regression model to predict PRICE is:
PRICE = 3,09,980.8034 + 17,945.0381Bedroom -2,595.9465Bathroom + 5,114.6350Cars + 7.3638SQ FT
The best regression model to predict PRICE is:
PRICE = 3,09,980.8034 + 17,945.0381*3 -2,595.9465*2 + 5,114.6350*8 + 7.3638*3,000
PRICE = $4,21,632.379
orchestra answered 1 year agoRelated Solutions
Price Bedroom Bathroom Cars SQ FT 298,000 3 2.5 0 1,566 319,900 3 2.5 0 2,000...
Price
Bedroom
Bathroom
Cars
SQ FT
298,000
3
2.5
0
1,566
319,900
3
2.5
0
2,000
354,000
3
2
2
0
374,900
4
2.5
0
2,816
385,000
4
2
0
0
389,000
3
2.5
0
2,248
399,000
4
3
0
2,215
415,000
3
2.5
0
3,188
444,900
3
2
0
2,530
450,000
3
2
0
1,967
465,000
4
3
0
2,564
340,000
4
2.5
0
2,293
275,000
3
2.5
2
1,353
425,000
3
2
0
1,834
250,000
3
2.5
0...
Consider a 100,000 sq. ft. building that will be acquired (at price $0) and demolished by...
Consider a 100,000 sq. ft. building that will be acquired (at
price $0) and demolished by local government at the end of 15
years. Assume the building is fully leased building
under an absolute net lease structure (all expenses paid by
tenant); Consider 2 leases:
15 year lease at
$15/ft./yr.
5 year lease at
$15/ft./yr.
Suppose that $15 is the market rate and that the forecasted rent
growth rate is 0% . Also suppose that the discount rate for
contractual lease...
department patient services revenue space (sq ft.) Housekeeping labor hours salary dollars General administration 10,000 2,000...
department
patient services revenue
space (sq ft.)
Housekeeping labor hours
salary dollars
General administration
10,000
2,000
$1,500,000
Facilities
20,000
5,000
3,000,000
Financial Services
15,000
3,000
2,000,000
Total
45,000
10,000
$6,500,000
Routine Care
$30,000,000
400,000
150,000
$12,000,000
Intensive Care
$4,000,000
40,000
30,000
$5,000,000
Diagnostic Services
$6,000,000
60,000
15,000
$6,000,000
Other Services
$10,000,000
100,000
25,000
$7,000,000
Total
$50,000,000
600,000
220,000
$30,000,000
Grand total
$50,000,000
645,000
230,000
$36,500,000
6.3 Assume that the hospital uses the direct method for cost
allocation. Furthermore, the cost...
Potential Gross Income 100,000 sq. ft for the coming year average rent $15.00 per ft. $ ...
Potential Gross Income 100,000 sq. ft for the coming year
average rent $15.00 per ft.
$ 1,500,000
Less Vacancy Allowance (average 8%)
$ (120,000)
Effective Gross Income
$ 1,380,000
Cleaning expenses (5% of net rev)
$ (69,000)
Insurance ($ 0.02 per dollar replacement, R.C. = $40 per ft.
$ (80,000)
Management & Maintenance (11% of revenue)
$ (151,800)
Reserve for Replacement (savings for major repairs)
$ (50,000)
Property Taxes ($0.10 per $100 of R.C.)
$
(4,000)
$ (354,800)
Estimated Net...
Potential Gross Income 100,000 sq. ft for the coming year average rent $15.00 per ft. $ ...
Potential Gross Income 100,000 sq. ft for the coming year
average rent $15.00 per ft.
$ 1,500,000
Less Vacancy Allowance (average 8%)
$ (120,000)
Effective Gross Income
$ 1,380,000
Cleaning expenses (5% of net rev)
$ (69,000)
Insurance ($ 0.02 per dollar replacement, R.C. = $40 per ft.
$ (80,000)
Management & Maintenance (11% of revenue)
$ (151,800)
Reserve for Replacement (savings for major repairs)
$ (50,000)
Property Taxes ($0.10 per $100 of R.C.)
$
(4,000)
$ (354,800)
Estimated Net...
1. Rooms in a house (Bedroom, Bathroom, Living Room, etc.) are an example of a variable...
1. Rooms in a house (Bedroom, Bathroom, Living Room, etc.) are
an example of a variable that follows which scale of
measurement?
a. ratio scale
b. interval scale
c. nominal scale
d. ordinal scale
2. The top 10 ranked jobs based on various criterion are listed
below. Here we are interested in looking at the stress rating of
each job (I picked the right one in terms of stress!...also note
how many jobs that are ranked...
Price (thousands of $) Size (sq. ft.) # of Bedrooms # of Baths Distance to Town...
Price (thousands of $)
Size (sq. ft.)
# of Bedrooms
# of Baths
Distance to Town Center
Garage Dummy (1=garage; 0=no garage)
Pool Dummy (1=pool; 0=no pool)
271.8
2100
2
2.5
9
1
0
221.1
2300
3
1.5
18
0
1
266.6
2400
4
2
13
1
0
292.4
2100
4
2
14
1
0
209
1700
2
1.5
8
1
0
270.8
2500
6
2
7
1
0
246.1
2100
4
2
18
1
0
194.4
2300
2
2...
Your company is using a plant of size 10,000 sq. ft. that was constructed in 2006...
Your company is using a plant of size 10,000 sq. ft. that was
constructed in 2006 for $300,000. The cost indices that correspond
to this size of a plant for 2006 and 2014 are 145 and 186
respectively. If the power-sizing exponent is 0.55, how much would
it cost to build a 40,000 sq. ft. warehouse in 2014?
Note: Answer would be $816,026. Please include complete
explanation and step-by-step solution.
Below is the C ++ code for a given assignment. An acre equal 43,560 sq ft....
Below is the C ++ code for a given assignment. An acre equal
43,560 sq ft. Im supposed to find the total number of acres within
a tract of land that is 391,876 sq ft. the program compiles and
runs just fine but I'm wondering if it would be better to use the
int data type instead? I used double for more accuracy. The
instructor didn't say we had to use any certain data type so I'm
asking purely for...
Consider the following pro forma for the next 4questionsPotential Gross Income 100,000 sq. ft...
Consider the following pro forma for the next 4
questions
Potential Gross Income 100,000 sq. ft for the coming year
average rent $15.00 per ft.
$ 1,500,000
Less Vacancy Allowance (average 8%)
$ (120,000)
Effective Gross Income
$ 1,380,000
Cleaning expenses (5% of net rev)
$ (69,000)
Insurance ($ 0.02 per dollar replacement, R.C. = $40 per ft.
$ (80,000)
Management & Maintenance (11% of revenue)
$ (151,800)
Reserve for Replacement (savings for major repairs)
$ (50,000)
Property Taxes ($0.10...
ADVERTISEMENT
ADVERTISEMENT
Latest Questions
- C++ C++ Write a definition for a structure type for records for CDs. The record contains...
- Research Question: Does the spatial ability differ by biological sex? (Use Data A) Null Hypothesis: Spatial...
- Write a method speedingTicket() that decides whether a driver should be given a ticket from a...
- Beasley Ball Bearings paid a $4 dividend last year. The dividend is expected to grow at...
- 7. In order to improve the network performance and security, ACLs is recommended. Please explain what...
- Noting that there has been an increasing interest in organic foodstuffs with increasing affluence, Mr Tommy...
- 1. the physical sites at which crossing over occurs are the.... A. chiasmata B. Centrioles C....
ADVERTISEMENT