The commercial division of a real estate firm is conducting a regression analysis of the relationship between I, annual gross rents (in thousands of dollars), and y, selling price (in thousands of dollars) for apartment buildings. Data were collected on severalproperties recently sold and the following computer output was obtained.ANOVAMSSignificance FRegression141587.6ResidualTotal51984.7CoefficientsStandard Errort StatP-valueIntercept20.0003.22136.21Apnual Gros7.2401.36215.29Rentsa. How many apartment buildings were in the sample?b. Write the éstimated regression equation (to 2 decimals if necessary).c. Use the t statistic to test the significance of the relationship at a 0.05 level of significance.What is the p-value? Use Table 2 of Appendix D.P-value is-Sclect your answer -What is your condusion?- Select your answer -d. Use the F statistic to test the significance of the relalionship at a 0.06 level uf significanct.Compute the F test slatistic (to 2 decimals).What is the p-value? Use Tae 4 of Appendix B.Pvalue is-Select your answer VWhat is your Londlusion?Select your answere. Predict the selling prie of an apartinent building with pruss antiual rtas of $50,000 (o 1 decimal)thousatds

Comment: As per the our company guidelines we are supposed to answer only three subparts. Kindly…

Answered: The commercial division of a real…

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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A clothing manufacturer wants to estimate the amount of scrap cloth generated each day by its fabric cutting machines. Eight potential independent variables have been identified. These include the following. = amount of cloth run through cutting machines (in square feet) X2 = machine cutting speed (in feet per minute) age of machine (in years) The manufacturer selects 6 of the candidate independent variables to use in a multiple regression model for estimating y, the amount of scrap cloth (in square feet). Using data collected from 24 different cutting machines operating on different days, the model y = Bo+B1*1 +B,x2+ + Bax, is fit to the data. Fill in the blanks in the analysis of variance (ANOVA) table associated with this model. Do all ... calculations to at least three decimal places.
A student used multiple regression analysis to study how family spending (y) is influenced by income (x1), family size (x2), and additions to savings (x3). The variables y, x1, and x3 are measured in thousands of dollars. The following results were obtained. ANOVA df SS Regression 3 45.9634 Residual 11 2.6218 Total Coefficients Standard Error Intercept 0.0136 x1 0.7992 0.074 x2 0.2280 0.190 x3 -0.5796 0.920 1. Write out the estimated regression equation for the relationship between the variables. Compute coefficient of determination. What can you say about the strength of this relationship? c. Carry out a test to determine whether y is significantly related to the independent variables. Use a 5% level of significance. Carry out a test to…
What mean physical health score would you expect in a group of 28-year-old women with a graduate degree?
A group of 13 health children and adolescents participated in a study designed to analyze the relationship between age (AGE in years) and average total sleep time (ATST in minutes). To obtain a measure for ATST, recordings were taken on each subject on three consecutive nights and then averaged. The results obtained are given below along with the corresponding scatter plot. The estimated regression line is Y-hat= 646.483 – 14.041x Interpret the slope and intercept of the estimated regression line. Is it meaningful?
A researcher interested in explaining the level of foreign reserves for the country of Barbados estimated the following multiple regression model using yearly data spanning the period 2001 to 2016: FR=a+BOIL+yEXP+8FDI Where FR = yearly foreign reserves ($000's), OIL = annual oil prices, EXP = yearly total exports ($000's) and FDI = annual foreign direct investment ($000's). The sample of data was processed using MINITAB and the following is an extract of the output obtained: Predictor Сoef StDev t-ratio p-value Constant 5491.38 2508.81 2.1888 0.0491 OIL 85.39 18.46 4.626 0.0006 EXP -377.08 112.19 0.0057 FDI -396.99 160.66 -2.471 ** S = 2.45 R-sq 96.3% R-sq (adj) 95.3% Analysis of Variance Source DF MS F Regression 1991.31 663.77 ?? Error 12 77.4 6.45 Total 15 a) What is dependent and independent variables? b) Fully write out the regression equation c) Fill in the missing values *', ***', '?'and ??' d) Hence test whether B is significant. Give reasons for your answer. e) Perform the F…
Data on 220 reported crimes is collected from district X in 2016. Suppose CS denotes the total cost to the state of offering crime protection services to this district (in thousand dollars), LEOP denotes the number of law enforcement officers on patrol, DTP denotes the damage to public and private property (in thousand dollars), CCTV denotes the number of CCTV cameras installed in the district, and Prison denotes the number of prison inmates The following table shows the results of a few regressions of the total cost to the state. Dependent variable: total cost to the state (in thousand dollars) Regressor (1) (2) (3) (4) 12.32 17.99 14.55 18.1 LEOP (0.52) (0.84) (2.25) (0.82) 0.73 0.59 0.75 DTP (0 12) (0.04) 0.73 (0.06) CCTV (0.13) 2.11 2.12 (0.39) 288.5 (4 14) Prison (0.5) 182.5 191.6 219.95 Intercept (11.52) (6.68) (5.26) 0.64 0.75 0.12 0.75 R 220 220 220 220 Heteroskedasticity-robust standard errors are given in parentheses under coefficients. Which of the following statements…
A student used multiple regression analysis to study how family spending (y) is influenced by income (x1), family size (x2), and additions to savings (x3). The variables y, x1, and x3 are measured in thousands of dollars. The following results were obtained. ANOVA df SS Regression 3 45.9634 Residual 11 2.6218 Total Coefficients Standard Error intercept 0.0136 x1 0.7992 0.074 x2 0.2280 0.190 x3 -0.5796 0.920 answer please : 1: Carry out a test to see if x3 and y are significantly related. Use a 5% level of significance.
A nonprofit analyst considered two independent variables as a predictor for the dependent variable Commitment, the percent of total expenses that are allocated to charitable services. The independent variables are Revenue, total revenue in billions of dollars, andEfficiency, the percent of private donations remaining after fundraising expenses. The regression analysis resulted in this ANOVA table. Determine whether there is a significant relationship between commitment and the two independent variables at the 0.01 level of significance. Source Degrees of Freedom Sum of Squares Mean Square F p-value Regression 2 3640.0416 1820.02 51.0429 <.0001 Error 87 3102.1301 35.66 Total 89 6742.1717 Determine the p-value. The p-value is ________ (Round to three decimal places as needed.)
Acrylamide is a chemical that is sometimes found in cooked starchy foods and which is thought to increase the risk of certain kinds of cancer. The paper "A Statistical Regression Model for the Estimation of Acrylamide Concentrations in French Fries for Excess Lifetime Cancer Risk Assessment"+ describes a study to investigate the effect of frying time (in seconds) and acrylamide concentration (in micrograms per kilogram) in french fries. The data in the accompanying table are approximate values read from a graph that appeared in the paper. Frying Acrylamide Time Concentration 150 240 240 270 300 300 150 125 + 195 185 135 275 USE SALT (a) Find the equation of the least-squares line for predicting acrylamide concentration using frying time. (Round your answers to four decimal places.) ŷ = (b) Does the equation of the least-squares line support the conclusion that longer frying times tend to be paired with higher acrylamide concentrations? Explain. O No, the least squares regression line…
A sales manager for an advertising agency believes there is a relationship between the number of contacts that a salesperson makes and the amount of sales dollars earned. A regression analysis shows the following results. Coefficients Standard Error t-Stat p-value Intercept -12.201 6.560 -1.860 0.100 Number of contacts 2.195 0.176 12.505 0.000 ANOVA df SS MS F Significance F Regression 1.00 |13,555.42 |13,555.42 156.38 0.00 Residual 8.00 693.48 86.68 Total 9.00 14,248.90 Assume that X = 33.4 and E(X – X) 2814.4. Rounding to one decimal place, the 95% confidence interval for 30 calls is
A market study found that the sales for a firm were related to advertising expenditure, as follows: Advertising Expenditure (Kshs ‘000’) Sales (Kshs ‘000’) 0 13 1 16 2 14 3 22 4 17 5 21 6 26 Required Draw a scatter diagram with the line of best fit to show the relationship. Determine the regression line equation for estimating the sales for a given level of advertising expenditure What is the estimated sale in thousand, if no advertising expenditure is incurred?
A student used multiple regression analysis to study how family spending (y) is influenced by income (x) family size (x2), and addition to savings(x3). The variables y, x1, and x3. The variables y, x1, and x3 are measured in thousands of dollars . The following results were obtained. ANOVA df SS Regression 3 45.9634 Residual 11 2.6218 Total Coefficient Standard Error Intercept 0.0136 X1 0.7992 0.074 X2 0.2280 0.190 X3 -0.5796 0.920 Write out the estimated regression equation for the relationship between the variables. Compute coefficient of determination. What can you say about the strength of this relationship? Carry out a test to determine whether y is significantly related to the independent variables. Use a 5% level of significant. Carry out a test to see if X3 and y are significantly related. Use a 5% level of significance

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