Question

A researcher try to predict the yield (y) of coffee trees based on different locations (x1,...

A researcher try to predict the yield (y) of coffee trees based on different locations (x1, x2, x3, and x4). If the following info is provided: n = 15, Total SS = 16382.17, SSR = 15913.04

(a) Write the regression model of the yield?

(b) Find the variance?

(c) Find R 2 ?

Homework Answers

Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
The following models are the results of fitting dependent variable, Y on five independents variables X1,...
The following models are the results of fitting dependent variable, Y on five independents variables X1, X2, X3, X4 and X5. The following data represent a regression output from the Minitab software. Comment on the significance of the model based on the statistics given. Hence, suggest the appropriate steps to obtain the best forecast model, and state the criteria (s) should be fulfill. The regression equation is Y = 19.3 + 4.607 X1 -- 0.725 X2 + 1.164 X3 +...
1. For the following multiple regression which was conducted to attempt to predict the variable based...
1. For the following multiple regression which was conducted to attempt to predict the variable based on the independent variables shown, answer the following questions. Regression Statistics Multiple R 0.890579188 R Square 0.793131289 Adjusted R Square 0.7379663 Standard Error 30.28395534 Observations 20 ANOVA df SS MS F Regression 4 52743.23074 13185.81 14.37743932 Residual 15 13756.76926 917.1179509 Total 19 66500 Coefficients Standard Error t Stat P-value Intercept 73.33291 62.25276 1.17799 0.25715 X1 -0.13882 0.05353 -2.59326 0.02037 X2 3.73984 0.95568 3.91328 0.00138...
2. Consider the data set has four variables which are Y, X1, X2 and X3. Construct...
2. Consider the data set has four variables which are Y, X1, X2 and X3. Construct a multiple regression model using Y as response variable and other X variables as explanatory variables. (a) Write mathematics formulas (including the assumptions) and give R commands to obtain linear regression models for Y Xi, i =1, 2 and 3. (b) Write several lines of R commands to obtain correlations between Xi and Xj , i 6= j and i, j = 1, 2,...
A researcher would like to predict the dependent variable Y from the two independent variables X1...
A researcher would like to predict the dependent variable Y from the two independent variables X1 and X2 for a sample of N=12 subjects. Using multiple linear regression, it has been confirmed that the overall regression model is statistically significant at α=0.05 with F(2,9)=5.66 (p=0.026). Calculate the 95% confidence intervals for both partial slopes. X1 X2 Y 66.2 60.5 75.2 41.6 19.3 26.9 52.5 57.2 50.4 60.9 42.5 44 75.2 49.3 71.6 63.9 57 56.5 36.8 62 45.6 38.5 61.4...
The owner of a movie theater company used multiple regression analysis to predict gross revenue (y)...
The owner of a movie theater company used multiple regression analysis to predict gross revenue (y) as a function of television advertising (x1)  and newspaper advertising (x2).  The estimated regression equation was ŷ = 83.8 + 2.26x1 + 1.50x2. The computer solution, based on a sample of eight weeks, provided SST = 25.8 and SSR = 23.385. (a) Compute and interpret  R2 and Ra2. (Round your answers to three decimal places.) The proportion of the variability in the dependent variable that can be...
The owner of a movie theater company used multiple regression analysis to predict gross revenue (y)...
The owner of a movie theater company used multiple regression analysis to predict gross revenue (y) as a function of television advertising (x1) and newspaper advertising (x2). The estimated regression equation was ŷ = 82.5 + 2.26x1 + 1.30x2. The computer solution, based on a sample of eight weeks, provided SST = 25.3 and SSR = 23.415. (a)Compute and interpret R2 and Ra2. (Round your answers to three decimal places.) The proportion of the variability in the dependent variable that...
The owner of a movie theater company used multiple regression analysis to predict gross revenue (y)...
The owner of a movie theater company used multiple regression analysis to predict gross revenue (y) as a function of television advertising (x1) and newspaper advertising (x2).The estimated regression equation was ŷ = 83.1 + 2.23x1 + 1.30x2. The computer solution, based on a sample of eight weeks, provided SST = 25.4 and SSR = 23.395. (a) Compute and interpret R2 and Ra2. (Round your answers to three decimal places.) The proportion of the variability in the dependent variable that...
A business statistics professor would like to develop a regression model to predict the final exam...
A business statistics professor would like to develop a regression model to predict the final exam scores for students based on their current GPAs, the number of hours they studied for the exam, the number of times they were absent during the semester, and their genders. The data for these variables are given in the accompanying table. Complete parts a through d below. Score   GPA   Hours   Absences   Gender 87   3.75   2.0   0   Female 77   3.20   4.5   3   Male 82   3.16  ...
y   x1   x2   x3   x4 64   74   22   24   17 43   63   29   15   30 51  ...
y   x1   x2   x3   x4 64   74   22   24   17 43   63   29   15   30 51   78   20   9   25 49   52   17   38   29 39   45   12   19   37 Consider the set of dependent and independent variables given below. Perform a best subsets regression and choose the most appropriate model for these data. Find the most appropriate model for the data. Note that the coefficient is 0 for any variable that is not included in the model. y= _____+...
Exercise 11. A researcher wants to develop a mathematical model that relates fuel efficiency (MPG), y,...
Exercise 11. A researcher wants to develop a mathematical model that relates fuel efficiency (MPG), y, to three variables: Engine size, x1, curb weight, x2, and horsepower, x3. Data are gathered from 13 randomly selected vehicles and listed in the table below. Find the multiple regression equation for the data. MPG, y Engine size, x1 Curb weight, x2 Horsepower, x3 24 2.4 3289 177 25 2.4 3263 158 24 2.5 3230 170 22 3.5 3580 272 18 2.8 3175 255...