A house developer company wants to investigate the influencing factors when the customersbuy a house. The developer went to a local real estate agency and obtained the dataconsisting of the following variables:Y = selling price of house (RM'000)X, = age of house (years)X, = lot size (100 square feet)X3number of bedroomsif intermediate lotX =0if corner lotRefer to Appendix 2 for the computer output.(a)Write down the fitted regression function.(b)If the customer plan to buy a 5 year old intermediate house that has a lot size of 1400square feet and 4 bedrooms, what price would you expect?(c)Does an increase in lot size by 100 square feet change the sales price by RM5000?Test by using the appropriate hypothesis, Use g =0,05. APPENDIX 2ModelUnstandardizedCoefficientsStd. Error1 Constant36.7462.14X8.9173.044X20.5271.312X361.4613.70X4-147.7019.05Analysis of VarianceSum ofModelSquaresdf1 Regression1457784Residual14877Total14577811Extra Sum ofSSRSquares128143dfX,112231X3]X1„X236461| X4X1„X2,X3127661

Given information: Model Unstandardised coefficients Beta Std. Error Constant 36.74 62.14…

Answered: A house developer company wants to…

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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11. What is the standard error of the slope of the regression line (SEb)? Please put the answer in bold.
The table below gives the number of hours seven randomly selected students spent studying and their corresponding midterm exam grades. Using this data, consider the equation of the regression line, yˆ=b0+b1xy^=b0+b1x, for predicting the midterm exam grade that a student will earn based on the number of hours spent studying. 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. Hours Studying 2 2.5 3 3.5 4 4.5 5 Midterm Grades 72 74 80 82 87 88 93 Find the value of the coefficient of determination. Round your answer to three decimal places.
The table below gives the number of hours five randomly selected students spent studying and their corresponding midterm exam grades. Using this data, consider the equation of the regression line, yˆ=b0+b1xy^=b0+b1x, for predicting the midterm exam grade that a student will earn based on the number of hours spent studying. 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. hours studying 0 1 3 4 5 grades 63 65 80 81 87 Find the value of the coefficient of determination. Round your answer to three decimal places.
You were asked to help with analysis of birth weights (BW) of 10,000 infants born in NYC during a certain period of time. The aim of the analysis is to see whether the birth weights of the infants are associated with mothers AGE at birth (continuous variable in years) and mothers smoking status (the maternal smoking status MSS contains 4 categories “Non-smoker”, “Past-smoker”, “Passive-smoker”, “Smoker”) and NYC boroughs (the BOROUGH variable contains 5 categories “Manhattan”, “Bronx”, “Brooklyn”, “Queens” and “Staten Island”). Questions: 1.Write down the population model that estimates BW based on variables AGE and BOROUGH(with the dummy variables). Make sure that it is clear what each predictor means. 2.How many parallel lines are computed by model from population model you created above? 3.Write down the population model that estimates BW based on variables AGE, MSS(with their dummy variables) and BOROUGH(with their dummy variables). Also write down the number of parrallel lines.…
The table below gives the number of hours seven randomly selected students spent studying and their corresponding midterm exam grades. Using this data, consider the equation of the regression line, yˆ=b0+b1xy^=b0+b1x, for predicting the midterm exam grade that a student will earn based on the number of hours spent studying. 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. Hours Studying 2 2.5 3 3.5 4 4.5 5 Midterm Grades 72 74 80 82 87 88 93 Find the estimated slope. Round your answer to three decimal places.
A frequent flyer was interested in the relationship between dollars spent on flying and the distance flown. She sampled 20 frequent flyers of a certain airline. She collected the number of miles flown in the previous year and the total amount of money the flyer spent. A regression line of distance flown on money spent was fit to the data: \hat y = 24000 + 10xy^=24000+10x. A person who spent $1000 is predicted to have flown:
For a regression line y^=mx+b, what does the Sum of Squares Due to Error measure? Select the correct answer below: the total variation in x that cannot be explained by variation in y the total variation in y that cannot be explained by the error, or residuals, for x the total variation in y that cannot be explained by the variation in x the total variation in x that cannot be explained by the error, or residuals, for y
The estimated regression equation for a model involving two independent variables and 10 observations follows. y = 33.0798 + 0.6071x1 + 0.7058x2 a. Interpret b₁ and b2 in this estimated regression equation (to 4 decimals). b₁ = - Select your answer - b₂ = - Select your answer - b. Estimate y when *₁ = 180 and ₂ = 310 (to 3 decimals).
The table below gives the number of hours seven randomly selected students spent studying and their corresponding midterm exam grades. Using this data, consider the equation of the regression line, yˆ=b0+b1xy^=b0+b1x, for predicting the midterm exam grade that a student will earn based on the number of hours spent studying. 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. Hours Studying 2 2.5 3 3.5 4 4.5 5 Midterm Grades 72 74 80 82 87 88 93 Determine if the statement "Not all points predicted by the linear model fall on the same line" is true or false.
26) Below is some of the regression output from a simple regression of the number of wins for a major league baseball team and the size amount of money the team is paying its players (expressed in millions of $'s) *fill in the blank table* Suppose that the team owner is trying to decide whether to pay a particular free agent player. Based on the player's previous statistics, the owner thinks that the new player can help his team increase the number of wins but the new player is going to cost more than the player he will be replacing. The owner decides it is a good idea to sign the new player if he can be pretty sure that the coefficient is at least 0.20. When testing this hypothesis, what is the test statistic? (please express your answer using 2 decimal places)
A grocery store manager did a study to look at the relationship between the amount of time (in minutes) customers spend in the store and the amount of money (in dollars) they spend. The results of the survey are shown below. Time 12 26 5 28 11 24 20 21 16 Money 37 84 34 84 53 92 72 92 75 The equation of the linear regression line is: ˆyy^ = + xx (Please show your answers to two decimal places) Use the model to predict the amount of money spent by a customer who spends 20 minutes at the store.Dollars spent = (Please round your answer to the nearest whole number.)
We wish to predict the salary for baseball players (y) using the variables RBI (x1) and HR (x2), then we use a regression equation of the form ˆy=b0+b1x1+b2x2y^=b0+b1x1+b2x2. HR - Home runs - hits on which the batter successfully touched all four bases, without the contribution of a fielding error. RBI - Run batted in - number of runners who scored due to a batters's action, except when batter grounded into double play or reached on an error Salary is in millions of dollars. The following is a chart of baseball players' salaries and statistics from 2016. Player Name RBI's HR's Salary (in millions) Adrian Beltre 104 32 18.000 Justin Smoak 34 14 3.900 Jean Segura 64 20 2.600 Justin Upton 87 31 22.125 Brandon Crawford 84 12 6.000 Curtis Granderson 59 30 16.000 Aaron Hill 38 10 12.000 Miquel Cabrera 108 38 28.050 Adrian Gonzalez 90 18 21.857 Jacoby Ellsbury 56 9 21.143 Mark Teixeira 44 15 23.125 Albert Pujols 119 31 25.000 Matt Wieters 66 17 15.800 Logan…

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