Excel > Data > Data Analysis > Regression
SUMMARY OUTPUT | ||||||||
Regression Statistics | ||||||||
Multiple R | 0.890072214 | |||||||
R Square | 0.792228546 | |||||||
Adjusted R Square | 0.772749972 | |||||||
Standard Error | 84800.48797 | |||||||
Observations | 36 | |||||||
ANOVA | ||||||||
df | SS | MS | F | Significance F | ||||
Regression | 3 | 8.77428E+11 | 2.92476E+11 | 40.67179427 | 4.99573E-11 | |||
Residual | 32 | 2.30116E+11 | 7191122761 | |||||
Total | 35 | 1.10754E+12 | ||||||
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | |
Intercept | 22155.45481 | 58258.39153 | 0.38029637 | 0.70623813 | -96513.00544 | 140823.9151 | -96513.00544 | 140823.9151 |
Sqft | 127.7049612 | 41.13793862 | 3.104311142 | 0.003972779 | 43.90972238 | 211.5002001 | 43.90972238 | 211.5002001 |
Beds | 23271.30456 | 24644.8608 | 0.944266018 | 0.352109179 | -26928.63415 | 73471.24327 | -26928.63415 | 73471.24327 |
Baths | 94285.18627 | 29845.19751 | 3.159140971 | 0.003445405 | 33492.50831 | 155077.8642 | 33492.50831 | 155077.8642 |
a)
Price = 22155.45+127.71*Sqft+23271.30*Beds+94285.19*Baths
Coefficients | |
Intercept | 22155.45 |
Sqft | 127.71 |
Beds | 23271.30 |
Baths | 94285.19 |
b-1)
b-2)
b-3)
c)
Given, sqft = 2382, Beds = 3 and Baths = 2
Price = 22155.45+127.71*Sqft+23271.30*Beds+94285.19*Baths
Price = 22155.4548+127.7050*2382+23271.3046*3+94285.1863*2 = 584732.9587 = $584733 (rounded)
6 Exercise 14-35 Algo 33.71 points A realtor in Arlington, Massachusetts, is analyzing the relationship between...
A realtor in Arlington, Massachusetts, is analyzing the relationship between the sale price of a home (Price), its square footage (Sqft), the number of bedrooms (Beds), and the number of bathrooms (Baths). She collects data on 36 recent sales in Arlington in the first quarter of 2009 for the analysis. The data is shown in the accompanying table Price 840,000 2,768 822,000 2,500 713,000 2,400 689,000 2,200 685,000 2,716 645,000 2,524 625,000 2,732 620,000 2,436 587,500 2,100 585,000 1,947 583,000...
Ches A realtor in Arlington, Massachusetts, is analyzing the relationship between the sale price of a home (Price in $), its square footage (Sqft), the number of bedrooms (Beds), and the number of bathrooms (Baths). She collects data on 36 sales in Arlington in the first quarter of 2009 for the analysis. A portion of the data is shown in the accompanying table. Price 672.000 569.077 Sqft 2,212 1.731 Beds Baths 5 1.0 11.5 307,500 850 1 1.0 Click here...
Exercise 14-35 Algo A realtor in Arington, Messschusetts, 1; 5no yzing the restionanla betw een tne saie price of 5 home Price In SI, ts "uner footage Gqft. tne number oroecrooms secsl, and tne number of oothrooms etnsl. Sne colects ast2 on 36 gsies 1n Arlington in the first quarter of 2009 for the analyss. A partionof the data s shown In the accompanying teble. 58,7 2,381.8 1 1.8 a. Estim te tne model Price . ·ySqt-o ,Bed; +63Bstn; ....
4a A real estate analyst believes that the three main factors that influence an apartment’s rent in a college town are the number of bedrooms, the number of bathrooms, and the apartment’s square footage. For 40 apartments, she collects data on the rent (y, in $), the number of bedrooms (x1), the number of bathrooms (x2), and its square footage (x3). She estimates the following model as Rent = β0 + β1Bedroom + β2Bath + β3Sqft + ε. The following...
Price
Sqft
Beds
Baths
Col
840000
2768
4
3.5
1
822000
2500
4
2.5
1
713000
2400
3
3
1
689000
2200
3
2.5
1
685000
2716
3
3.5
1
645000
2524
3
2
1
625000
2732
4
2.5
0
620000
2436
4
3.5
1
587500
2100
3
1.5
1
585000
1947
3
1.5
1
583000
2224
3
2.5
1
569000
3262
4
2
0
546000
1792
3
2
0
540000
1488
3
1.5
0
537000
2907
3
2.5
0...
A real estate analyst estimates the following regression, relating a house price to its square footage (Sqft): PriceˆPrice^ = 48.11 + 52.06Sqft; SSE = 56,244; n = 50 In an attempt to improve the results, he adds two more explanatory variables: the number of bedrooms (Beds) and the number of bathrooms (Baths). The estimated regression equation is PriceˆPrice^ = 28.82 + 40.84Sqft + 10.34Beds + 16.65Baths; SSE = 48,681; n = 50 Calculate the value of the test statistic. (Round...
please show the steps and the
code to solve this in R, thank you
11. (10 marks) (using dataset: "hpricel", in R: data(hprice1, package-wooldridge')) Use the data to 5 estimate the model where price is the house price measured in thousands of dollars iWrite out the results in equation form. iiWhat is the estimated increase in price for a house with one more bedroom, holding square footage and lot size constant? iii What is the estimated increase in price for...
QUESTION 27 Q27. A manager at a local bank analyzed the relationship between monthly salary (y, in $) and length of service (x, measured in months) for 30 employees. She estimates the model: Salary = Bo + B1 Service + ε. The following ANOVA table below shows a portion of the regression results. df SS M S F Regression 555,420 555,420 7.64 Residual 27 1,962,873 72,699 Total 28 2 ,518,293 Coefficients Standard Error t-stat p-value Intercept 784.92 322.25 2.44 0.02...
Exercise 14-27 Algo A social scientist would like to analyze the relationship between educational attainment (in years of higher education) and annual salary (in $1,000s). He collects data on 20 individuals. A portion of the data is as follows ts Salary 37 Education 6 69 eBook 29 Print I Click here for the Excel Data File References a. Find the sample regression equation for the model: Salary Ao AEducation . (Round answers to 2 decimal places.) Salary Education b. Interpret...
Please show all work need help with ALL parts part of one question
Assignment 3 [Read-Onlyl Word View ? Tell me Share File Home Insert Design Layout References Mailings Review Outline Draft New WindowE Arrange All Switch Macros Properties Windows Web Side Show Zoom 100% Read ode Layout Layout Learning Tools to Side Split Macros SharePoint Views Immersive Page Movement Part (b) (2 points) Interpret the estimated value of the intercopt, i.e,explain what the number means in this regression Part...