### TABLE 15-3In Hawaii, condemnation proceedings are underway to enable private citizens to own the property that their homes are built on. Until recently, only estates were permitted to own land, and homeowners leased the land from the estate. In order to comply with the new law, a large Hawaiian estate wants to use regression analysis to estimate the fair market value of the land. The following model was fit to data collected for n = 20 properties, 10 of which are located near a cove.\[ Y = \text{Sale price of property in thousands of dollars}\]\[ X1 = \text{Size of property in thousands of square feet}\]\[ X2 = \text{1 if property located near cove, 0 if not}\]Using the data collected for the 20 properties, the following partial output obtained from Microsoft Excel is shown:### SUMMARY OUTPUT#### Regression Statistics- **Multiple R**: 0.985- **R Square**: 0.970- **Standard Error**: 9.5- **Observations**: 20#### ANOVA| | df | SS | MS | F | Signif F ||----------|----|-------|-------|------|-----------|| Regression | 5 | 28324 | 5664 | 6.2 | 0.03001 || Residual | 14 | 1279 | 91 | | || Total | 19 | 29063 | | | |#### Coefficients| | Coeff | StdError | t Stat | P-value ||----------|-------|----------|--------|----------|| Intercept | -32.1 | 35.7 | -0.90 | 0.3834 || Size | 12.2 | 5.9 | 2.05 | 0.0594 || Cove | -104.3| 53.5 | -1.95 | 0.10715 || Size*Cove | 17.0 | 8.5 | 1.99 | 0.10661 || SizeSq | 0.3 | 0.

From the given output,The p value corresponding with F statistic is 0.03001Alpha=0.05

Answered: In Hawaii, condemnation proceedings are…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Accountants at the GIll Co and Charted Brothers Accounting believed that several traveling executives were submitting unusually high travel vouchers upon returning from business trips. First, they took a sample of 200 vouchers submitted from the past year. Then they developed the following multiple-regression equation relating expected travel cost (Y) to a number of days on the road (X1) and distance traveled (X2) in miles: Y = 90.00 + 48.50X1 + 0.40X2 Here is additional information concerning the regression model: Sb1 = 0.038 Sb2 =0.019 R2 = 0.68 Se = 1.63 F-Statistic = 32.123 Durbin-Watson (d) statistic = 0.5436 a. Which of the independent variables appear to be statistically significant (at the 0.05 significant level) in explaining the expected travel cost for accountants
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In the section we introduced a descriptive measure of the utility of the multiple linear regression for making predictions. a. Define and interpret this descriptive measure. b. Identify the symbol used for this descriptive measure.
Stoaches are fictional creatures that nest in truffula forests. A researcher wants to know whether there is a relationship between a stoach’s wingspan (?W, the predictor) and its nest height (?H, the response). A sample of 85 stoaches is observed, and for each, the wing-span (in cm) and the nest height (in m) are recorded. The observed data meet the assumptions for a linear regression, so the researcher fits the regression model and obtains a regression equation ℎ̂=−4.273+0.834?,h^=−4.273+0.834w, with standard error for the coefficient of ?w equal to 0.242. Determine the ?p-value from a test for a statistically significant linear dependence of nest height on wing-span. (Give your answer to 4 decimal places.
1. School administrators believe their freshman applications are influenced by two variables: tuition and the size of the applicant pool of eligible high school seniors in the state. The following data for an 8-year period show the tuition rates (per semester) and the sizes of the applicant pool for each year: Tuition in pesos Applicants Pool Applicants 27000 76,200 11,060 37500 78,050 10,900 41250 67,420 8,670 42000 70,390 9.050 46500 62,550 7,400 48750 59,230 7,100 52500 57,900 6,300 57900 60,080 6,100
A box office analyst seeks to predict opening weekend box office gross for movies. Toward this goal, the analyst plans to use online trailer views as a predictor. For each of the 66 movies, the number of online trailer views from the release of the trailer through the Saturday before a movie opens and the opening weekend box office gross (in millions of dollars) are collected and stored in the accompanying table. A linear regression was performed on these data, and the result is the linear regression equation Yi=−1.254+1.3968Xi. Complete parts (a) through (d). a. Determine the coefficient of determination,r2,and interpret its meaning. b. Determine the standard error of the estimate. c. How useful do you think this regression model is for predicting opening weekend box office gross? d. Can you think of other variables that might explain the variation in opening weekend box office gross?
Suppose the following data were collected from a sample of 1515 CEOs relating annual salary to years of experience and the economic sector their company belongs to. Use statistical software to find the following regression equation: SALARYi=b0+b1EXPERIENCEi+b2SERVICEi+b3INDUSTRIALi+eiSALARY�=�0+�1EXPERIENCE�+�2SERVICE�+�3INDUSTRIAL�+��. Is there enough evidence to support the claim that on average, CEOs in the service sector have lower salaries than CEOs in the financial sector at the 0.010.01 level of significance? If yes, write the regression equation in the spaces provided with answers rounded to two decimal places. Else, select "There is not enough evidence." Copy Data CEO Salaries Salary Experience Service (1 if service sector, 0 otherwise) Industrial (1 if industrial sector, 0 otherwise) Financial (1 if financial sector, 0 otherwise) 144225144225 1010 11 00 00 187765187765 2020 00 00 11 142500142500 66 11 00 00 169650169650 2828 11 00 00 167250167250 3131 00…
1) Draw the graph of the estimated regression below. Y₁ = Bo + B₁X₁B₂X² + B3X²
The registrar at State University believes that decreases in thenumber of freshman applications that have been experiencedare directly related to tuition increases. They have collectedthe following enrollment and tuition data for the past decade: a. Develop a linear regression model for these data andforecast the number of applications for State Universityif tuition increases to $10,000 per year and if tuition islowered to $7000 per year.b. Determine the strength of the linear relationship betweenfreshman applications and tuition using correlation. c. Describe the various planning decisions for State Univer-sity that would be affected by the forecast for freshman applications.

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