d. Use the F statistic to test the significance of the relationship at a .05 level ofsignificance.Compute the F test statistic (to 2 decimals).What is the p-value? Use Table 1 of Appendix B.p-value is SelectWhat is your conclusion?Selecte. Predict the selling price of an apartment building with gross annual rents of$50,000 (to 1 decimal).$thousands. The commercial division of a real estate firm is conducting a regression analysisof the relationship between x, annual gross rents (in thousands of dollars), andy, selling price (in thousands of dollars) for apartment buildings. Data werecollected on several properties recently sold and the following computer outputwas obtained.The regression equation isY = 20.0 + 7.25 XPredictorСoefSE CoefConstant20.0003.22136.217.2501.36285.29Analysis of VarianceSOURCEDFSSRegression141,587.1Residual Error7Total851,984.5a. How many apartment buildings were in the sample?b. Write the estimated regression equation (to 2 decimals if necessary).+c. What is the value of sb1 (to 4 decimals)?

a. The total degrees of freedom is 8. The number of apartment buildings were in the sample is,…

Answered: a. How many apartment buildings were in…

a. How many apartment buildings were in the sample? b. Write the estimated regression equation (to 2 decimals if necessary). + %3D c. What is the value of sp1 (to 4 decimals)?

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

a. Estimate the regression line and also write the prediction equation. y = 83.4578-5.8795 x y = 5.8795 + 83.4578 x ŷ ŷ= = -5.8795 + 83.4578 x = 83.4578 + 5.8795 x
The arm span and foot length were both measured (in centimeters) for each of 20 students in a biology class. The computer output displays the regression analysis. Which of the following is the best interpretation of the coefficient of determination r2? About 37% of the variation in arm span is accounted for by the linear relationship formed with the foot length. About 65% of the variation in foot length is accounted for by the linear relationship formed with the arm span. About 63% of the variation in arm span is accounted for by the linear relationship formed with the foot length. About 63% of the variation in foot length is accounted for by the linear relationship formed with the arm span.
Using the weights (Ib) and highway fuel consumption amounts (mi/gal) of the 48 cars listed in the accompanying data set, one gets this regression equation: y = 58 9-0.00749x, where x represents weight Complete parts (a) through (d). Click the icon to view the car data. 東 b. What are the specific values of the slope and y-intercept of the regression line? O A. The slope is 58.9 and the y-intercept is 0.007499. B. The slope is -0.00749 and the y-intercept is 58.9. O C. The slope is 58.9 and the y-intercept is -0.00749. O D. The slope is 0.00749 and the y-intercept is 58.9. c. What is the predictor variable? O A. The predictor variable is highway fuel consumption, which is represented by x. B. The predictor variable is weight, which is represented by x. O C. The predictor variable is weight, which is represented by y O D. The predictor variable is highway fuel consumption, which is represented by y. d. Assuming that there is a significant linear correlation between weight and highway fuel…
Hazel has four very short children and wants to predict how tall the kids will be in the future, as they get older she measures their height and finds: Rufus, age 3, 46 cm in height Angus, age 4, 52 cm in height matilda, age 6, 63 cm in height Lao age 8, 85 cm in height Round to the nearest integers, what is the regression equation computed from the data
Using your favorite statistics software package, you generate a scatter plot with a regression equation and correlation coefficient. The regression equation is reported as y = - 13.31a + 55.86 and the r = 0.819. What proportion of the variation in y can be explained by the variation in the values of x? r2 = % Report answer as a percentage accurate to one decimal place. Submit Question M hp % & 7 08 16 5. %23 3m
In multiple regression, when all independent variables are considered but the order in which they are added to the model is determined by the amount it contributes to the dependent variable, it is called: a.Two step b.Stepwise c.Simultaneous d.Backward step
2. Participants were kept awake for a certain number of hours before given a visuospatial task. Researchers measured how many correct responses each participant had. Results are shown below. Use alpha = .01. Number of Correct Hours Kept Awake (X) Responses (Y) 21 X = 10 SS, = 422 Y = 10 SS, = 690 2 4 19 %3D 6. 13 SPxy =-525 ху 5 20 S, =5.70 S, = 7.29 9. 11 10 9. 14 5 15 5 17 2 18 1 17 1 13 4 18 8 11 A. Graph the data. B. State the hypotheses. C. Make a decision about the null. a. Calculate Pearson's r i. Decision about null hypothesis? b. Calculate effect size i. Interpret effect size. D. State your conclusion. E. Relate your conclusion to the research. F. Calculate the regression formula. G. If someone was kept awake for 9 hours, what is the predicted number of correct responses?
A researcher is interested in understanding the relationship between ife stress (Variable X) and quality of life (Varlable Y). Using the whiteboard, plot the data below Into a scatterplot and comment on the type of relationship you see between life stress and quality of life. BE SURE AND SAVE YOUR PICTURE. 3. 3. Aa stroke
Bluereef real estate agent wants to form a relationship between the prices of houses, how many bedrooms, House size in sq ft and Lot Size in sg ft. The data pertaining to 100 houses were processed using MINITAB and the following is an extract: The regression equation is Price = B + ÞBedroom + yHouse Size + ALot Size Predictor Coef SE Coef T P Constant 37718 14177 2.66 ** Bedrooms 2306 6994 0.33 0.742 House Size 74.3 52.98 0.164 Lot Size -4.36 17.02 -0.26 0.798 s= 25023 R-Sq=56.0% R-Sq(adj)=54.6% Source DF MS F P Regression Residual 3 76501718347 25500572782 **** Error 96 60109046053 626135896 Total 99 1. Fill in the missing values *, **, and **** 2. Use the p-value approach to determine if o is significant at the 5% significance level
A regression was run to determine if there is a relationship between hours of TV watched per day, xx, and number of sit-ups, yy, a person can do in a minute.The results of the regression were: y=ax+b a=-1.399 b=26.311Use this to predict the number of sit-ups a person who watches 12.512.5 hours of TV can do in a minute. Round to the nearest whole number.