Question
In: Math
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 | 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 |
- Plz do all the calculations on excel n show the excel files.
- Construct and interpret a correlation matrix for your data.
- Show the step wise process of determining the best regression model to predict PRICE Anova. EXPLAIN the process as you move from the full model to your final model.
- Using your final model, select values for the independent variables and predict the house’s sales price.
Solutions
Expert Solution
data -> data analysis -> correlation
| Price | Bedroom | Bathroom | Cars | SQ FT | |
| Price | 1 | ||||
| Bedroom | 0.1163 | 1 | |||
| Bathroom | 0.0693 | 0.4544 | 1 | ||
| Cars | -0.0119 | -0.2773 | -0.1439 | 1 | |
| SQ FT | 0.1825 | -0.1648 | 0.0818 | -0.1522 | 1 |
with Price, there is weak correlation with every independent variable
SQ FT has highest correlation with Price
Bathroom and Bedroom has correlation 0.4544
data -> data analysis -> regression
| SUMMARY OUTPUT | |||||
| Regression Statistics | |||||
| Multiple R | 0.2449 | ||||
| R Square | 0.0600 | ||||
| Adjusted R Square | -0.1280 | ||||
| Standard Error | 63973.0562 | ||||
| Observations | 25 | ||||
| ANOVA | |||||
| df | SS | MS | F | Significance F | |
| Regression | 4 | 5222651649.4394 | 1305662912.3598 | 0.3190 | 0.8619 |
| Residual | 20 | 81851038446.5607 | 4092551922.3280 | ||
| Total | 24 | 87073690096.0000 | |||
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | |
| Intercept | 309980.8034 | 90752.3457 | 3.4157 | 0.0027 | 120674.7275 |
| Bedroom | 17945.0381 | 25574.4249 | 0.7017 | 0.4910 | -35402.2774 |
| Bathroom | -2595.9465 | 28990.2834 | -0.0895 | 0.9295 | -63068.6180 |
| Cars | 5114.6350 | 16897.8149 | 0.3027 | 0.7653 | -30133.5893 |
| SQ FT | 7.3638 | 7.4722 | 0.9855 | 0.3362 | -8.2230 |
see the column p-value
we observe that all independent variable has p-value > 0.05
hence they all are insignificant
lowest p-value is of SQ Ft
so we just include this
| SUMMARY OUTPUT | |||||
| Regression Statistics | |||||
| Multiple R | 0.182509324 | ||||
| R Square | 0.033309653 | ||||
| Adjusted R Square | -0.008720362 | ||||
| Standard Error | 60495.52468 | ||||
| Observations | 25 | ||||
| ANOVA | |||||
| df | SS | MS | F | Significance F | |
| Regression | 1 | 2900394438 | 2900394438 | 0.792520615 | 0.382556796 |
| Residual | 23 | 84173295658 | 3659708507 | ||
| Total | 24 | 87073690096 | |||
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | |
| Intercept | 368173.8051 | 21041.84324 | 17.49722213 | 8.72146E-15 | 324645.4359 |
| SQ FT | 5.970685713 | 6.706855155 | 0.890236269 | 0.382556796 | -7.903501245 |
y^ = 368173.8051 + 5.9707 SQ FT
milcah answered 3 months agoRelated Solutions
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...
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...
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...
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...
Standard Quantity Standard Price (Rate) Standard Unit Cost Direct materials (cork board) 3.50 sq. ft. $...
Standard Quantity
Standard Price (Rate)
Standard Unit Cost
Direct materials (cork board)
3.50
sq. ft.
$
2.00
per sq. ft.
$
7.00
Direct labor
1
hrs.
$
13.00
per hr.
13.00
Variable manufacturing overhead (based on direct labor
hours)
1
hrs.
$
0.60
per hr.
0.60
Fixed manufacturing overhead ($67,500 ÷ 150,000 units)
0.45
Bullseye has the following actual results for the month of
September:
Number of units produced and sold
130,000
Number of square feet of corkboard used
470,000...
A sample of 24 recently sold. The variables are: the sale price in $/10000 (Y), the size of the home in sq. ft./1000 (X1), and the number of rooms (X2).
29.5
1.5
7
27.9
1.175
6
25.9
1.232
6
29.9
1.121
6
29.9
0.988
6
30.9
1.24
7
28.9
1.501
6
35.9
1.225
6
31.5
1.552
6
31
0.975
5
30.9
1.121
6
30
1.02
5
36.9
1.664
8
41.9
1.488
7
40.5
1.376
6
43.9
1.5
7
37.5
1.256
6
37.9
1.69
6
44.5
1.82
8
37.9
1.652
6
38.9
1.777
8
36.9
1.504
7
45.8
1.831
8
25.9
0.998
7
A sample of 24 recently sold. The...
A 0% grade meets a 3% grade at station 24+00.00 and an elevation of 372.15 ft....
A 0% grade meets a 3% grade at station 24+00.00 and an elevation
of 372.15 ft. For a passing sight distance of 2,000 ft, find the
following:
a. Minimum length of the vertical curve that allows for passing
using the minimum curve length equations.
b. Calculate the elevation of the middle point of the curve.
c. Calculate the elevation of the road at station 23+00.00.
Price ($) Quantity Demanded Quantity Supplied 0 25 0 1 21 1 2 17 3 3...
Price ($)
Quantity
Demanded
Quantity
Supplied
0
25
0
1
21
1
2
17
3
3
13
6
4
9
9
5
5
12
6
1
15
7
0
18
Question: Suppose the government sets a price in this market at
$2.
a. Is this a price floor or a price ceiling?
b. Does this create a shortage or surplus?
c. What is the difference in quantity demanded at this $2 price
relative to the market price?
d. What is...
3 The ten most recent cars sold at a dealership have an average price of $24,525...
3 The ten most recent cars sold at a dealership have an
average price of $24,525 with a standard deviation of s = $450.
Assuming that the prices of all cars sold by the dealership have an
approximately normal distribution, find the 98% confidence interval
for the mean price of all cars sold by the dealership, to the
nearest dollar.
Conclusion: We can be ___________confident that the mean
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________________...
Single data values (in hours): 3, 1, 4, 5, 5, 2, 2.5, 3.5, 4, 4.5, 0,...
Single data values (in hours): 3, 1, 4, 5, 5, 2, 2.5, 3.5, 4,
4.5, 0, 2, 2, 2.5, 3.5, 4, 4, 4, 4, 2, 3.5, 3.5, 2, 3, 4, 4, 3, 3,
3, 1
Claim: It was found that the mean time spent watching TV daily
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Null Hypothesis:...
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