We conduct a regression of size on hhinc, owner, hhsize1, hhsize2, and hhsize3. Wedo not include the constant. The regression output is reported in Table 3. Would youconclude that the home size increases with the household size? Interpret the signand magnitude of the estimated coefficients of hhsize1, hhsize2, and hhsize3 Table 3. regress size hhánc owner hhsizel hhsizez hhsize3, robust noconstantLinear regressionNumber of obs5,407F(5, 5402)11317.91Prob > F0.0000R-squared0.9157Root MSE348.5Robustsize Coefficient std. err.P>|t|(95% conf. interval]hhinc.005163.000497618.380.000.0041875.0061384Owner374.504910.6921935.030.000353.5439395.4659hhsizel647.899412.7997350.620.000622.8068672.992hhsize27.3956רר21.4297736.280.000735.3846819.4065hhsize3930.348929.3455631.700.000872.8197987.878 The questions below are based on a dataset containing the characteristics of 5,407households. In particular, we will use the following variables:- size: home size, measured in square feet.- hhinc: annual household net income, measured in euros.- owner. dummy variable equal to 1 if the living space is owned, and 0 if the livingspace is rented.- hhsize1: dummy variable equal to 1 if the number of household's members is 1 or2, and 0 otherwise.hhsize2: dummy variable equal to 1 if the number of household's members is 3 or4, and 0 otherwise.hhsize3: dummy variable equal to 1 if the number of household's members is 5 orabove 5, and 0 otherwise.- edu: education level of household's members.The Appendix contains tables with the critical values of the standard normal distribution andthe F distribution.

From the given output, The coefficient of hhsize1 is 647.8994. The coefficient of hhsize2 is…

Math

Statistics

We conduct a regression of size on hhinc, owner, hhsize1, hhsize2, and hhsize3. We do not include the constant. The regression output is reported in Table 3. Would you conclude that the home size increases with the h

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

Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find the regression equation, letting the fight arm blood pressure be the predictor (x) variable. Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 90 mm Hg. Use a significance level of 0.05. Right Arm 102 94 80 79 Left Arm 177 172 143 143 143 Click the icon to view the critical values of the Pearson correlation coefficient r The regression equation is y = 35.5+ 1.36 x. (Round to one decimal place as needed.) Given that the systolic blood pressure in the right arm is 90 mm Hg, the best predicted systolic blood pressure in the left arm is mm Hg. H T 101 6 & 7 4 L' 101 √₁ √ 1. (,) Copyright ©2022 Pearson Education Inc. All rights reserved. Terms of Use | Privacy Policy | Permissions | Contact Us | U H J 8 K fio More P 87°F Next + X insert (4) prt sc backspace 7:50 PM 8/5/202 enter delet ho
please do all parts! The estimated regression equation for this data set is y=4.4878+1.9549x. Part A: (in image) Part B: is the linear function is the appropriate regression function for this data set? Part C: do the residuals have a constant variance? Part D: are the residuals independent? Part E: are the error terms are normally distributed? y x22 821 818 846 2241 2254 2276 3258 3268 32
Write a multiple regression equation that can be used to analyze the data for a two-factorialdesign with two levels for factor A and three levels for factor B. Define all variables.
The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 63 inches. Is the result close to the actual weight of 462 pounds? Use a significance level of 0.05. Chest size (inches) Weight (pounds) 58 50 65 59 59 48 414 312 499 450 456 260 Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? y =+x (Round to one decimal place as needed.) What is the best predicted weight of a bear with a chest size of 63 inches? The best predicted weight for a bear with a chest size of 63 inches is pounds. (Round to one decimal place as needed.) Is the result close to the actual weight of 462 pounds? O A. This result is very close to the actual weight of the bear. O B. This result is close to the actual weight of the bear. O C. This result is not very close to the actual weight of the bear. O D.…
The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted w Click to copy table. a chest size of 58 inches. Is the result close to the actual weight of 632 pounds? Use a significance level of 0.05. Chest size (inches) Weight (pounds) 46 57 53 41 40 40 384 580 542 358 306 320 Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? y = + x (Round to one decimal place as needed.) What is the best predicted weight of a bear with a chest size of 58 inches? The best predicted weight for a bear with a chest size of 58 inches is pounds. (Round to one decimal place as needed.) Is the result close to the actual weight of 632 pounds? A. This result is close to the actual weight of the bear. B. This result is very close to the actual weight of the bear. C. This result is exactly the same as the actual weight of the bear. D.…
The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 58 inches. Is the result close to the actual weight of 672 pounds? Use a significance level of 0.05. Chest size (inches) Weight (pounds) 46 57 53 41 40 40 384 580 542 358 306 320
%3D Example 8. Given the regression lines as 3x + 2y = 26 and 6x + y = 31. %3D Find their point of intersection and interpret it. Also find the correlation coefficient between x and y.
Consider a regression model. The coefficient of determination (R2) gives the proportion of the variability in the dependent variable that is explained by the regression equation. True False
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The table below shows the heights (in feet) and the numbe of stories of six notable buildings in a city. Height, x Stories, y 778 621 519 510 494 473 (a) x = 500 feet (c) x = 318 feet (b) x = 649 feet (d) x = 727 feet 51 47 45 41 38 36 Find the regression equation.
a tab = The table below gives the number of hours spent unsupervised each day as well as the overall grade averages for seven randomly selected middle school students. Using this data, consider the equation of the regression line, bo + bx, for predicting the overall grade average for a middle school student based on the number of hours spent unsupervised each day. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, In practice, It would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Answer How to enter your answer (opens in new window) esc Step 3 of 6: Substitute the values you found in steps 1 and 2 into the equation for the regression line to find the estimated linear model. According to this model, if the value of the independent variable is increased by one unit, then find the change in the dependent variable . Google Play Store alt 1…
The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 4141 inches. Is the result close to the actual weight of 273273 pounds? Use a significance level of 0.05. Chest size (inches) 4040 5353 3838 4343 4444 5858 Weight (pounds) 227227 360360 153153 206206 234234 414414 LOADING... Click the icon to view the critical values of the Pearson correlation coefficient r. Question content area bottom Part 1 What is the regression equation? ModifyingAbove y with caretyequals=enter your response hereplus+enter your response herex (Round to one decimal place as needed.) Part 2 What is the best predicted weight of a bear with a chest size of 4141 inches? The best predicted weight for a bear with a chest size of 4141 inches is enter your response here pounds. (Round to one…
please view the information listed in the photos and answer the questions in both the photos! thank you :)