Q1: A researcher try to predict the yield (y) of coffee trees based on different locations...
Q1: 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 R2?
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Q1: A researcher try to predict the yield (y) of coffee trees
based on different locations...
4. A researcher built a model to predict an indicator of fitness using heart-rate (X1), weight...
4. A researcher built a model to predict an indicator of fitness using heart-rate (X1), weight (X2), height (X3) and age (X4) as predictors. The model was Y = 4 - 1.2 X1 -0.5 X2 +0.6 X3-0.2X4. The standard errors for X1, X2, X3, and X4 were 0.4, 0.3, 0.5, and 0.06 respectively. 1. If SSR=15500, R2 is 0.333 and F-stat is 5, complete the ANOVA table. 2. Which of these variables is statistically the most significant? Why?
Additional Problem A researcher collected data on Y and four X-variables: X1, X2, X3, X4, and he ...
Additional Problem A researcher collected data on Y and four X-variables: X1, X2, X3, X4, and he wants to obtain a regression model. However, he is not sure if all the four X-variables should be included in the model. He provides you with the information shown below, namely, the SSR obtained when Y was regressed on each subset of X-variables. Also given: SST-100, and that the sample size is n 12. Your task Apply the Forward-Stepwise selection method, with a-to-enter-...
ek-tin Based on the following regression output, what proportion the total variation in Y is explained...
ek-tin
Based on the following regression output, what proportion the total variation in Y is explained by X? Regression Statistics Multiple R 0.917214 R Square 0.841282 Adjusted R Square 0.821442 Standard Error 9.385572 Observations 10 ANOVA di SS MS Significance F 1 Regression 3735.3060 3735.30600 42.40379 0.000186 Residual 8 704.7117 88.08896 9 Total 4440.0170 Coefficients Standard Error t Stat P-value Lower 95% Intercept 31.623780 10.442970 3.028236 0.016353 7.542233 X Variable 1.131661 0.173786 6.511819 0.000186 0.730910 o a. 0.917214 o b.9.385572...
A researcher developed a regression model to predict the tear rating of a bag of coffee...
A researcher developed a regression model to predict the tear rating of a bag of coffee based on the plate gap in bag-sealing equipment. Data were collected on 2828 bags in which the plate gap was varied. An analysis of variance from the regression showed that b1equals=0.79240.7924 and Upper S Subscript b 1Sb1equals=0.20940.2094. a. At the 0.05 level of significance, is there evidence of a linear relationship between the plate gap of the bag-sealing machine and the tear rating of...
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=10 subjects. Use multiple linear regression to calculate the coefficient of multiple determination and test statistics to assess the significance of the regression model and partial slopes. Use a significance level α=0.02. X1 X2 Y 40.5 62.9 21.8 16.4 51.3 31.8 62.5 44.4 29.6 60.4 53.6 40.6 50.2 54 33.7 39.2 51.5 37 80.9 16.9 58.1 41.6 52.6...
question #1 A-D. Please show work. Q1. The following Regression function has been developed to check...
question #1 A-D. Please show work.
Q1. The following Regression function has been developed to check the relationship between the dependent variable y and the independent variable x1. Consider the following Minitab output and answer the questions. Regression Equation 9 = 0.86 + 0.65 x1 a) (4pt). Please fill out the Coefficients table appropriately. Coefficients Term Coef SE Coef T-Value P-Value VIF Constant (1) 1.38 16.58 0.000 X1 (ii) 0.231 7.00 0.000 1.00 b) (4pt). Please fill out the ANOVA...
4) Repair time of a car can be modeled by linear regression using months since the type of repair (X1), drive type (X2), servicing frequency (X3), and driving frequency (X4) as predictors. The model o...
4) Repair time of a car can be modeled by linear regression using months since the type of repair (X1), drive type (X2), servicing frequency (X3), and driving frequency (X4) as predictors. The model obtained was Y = 2.5 +1.7X1 – 3.5X2 + 6.2X3 – 4.7X4. The model was built based on 40 cars and the standard errors for X1, X2, X3, and X4 were 3.4, 2.6, 2.8, and 3.9 respectively. If the F-stat is 5.8, a) Find R2. b)...
4. Testing for significance Aa Aa Consider a multiple regression model of the dependent variable y on independent variables x1, x2, X3, and x4: Using data with n = 60 observations for each of the var...
4. Testing for significance Aa Aa Consider a multiple regression model of the dependent variable y on independent variables x1, x2, X3, and x4: Using data with n = 60 observations for each of the variables, a student obtains the following estimated regression equation for the model given: 0.04 + 0.28X1 + 0.84X2-0.06x3 + 0.14x4 y She would like to conduct significance tests for a multiple regression relationship. She uses the F test to determine whether a significant relationship exists...
Consider a multiple regression model of the dependent variable y on independent variables x1, X2, X3, and x4: Using data with n 60 observations for each of the variables, a student obtains the follow...
Consider a multiple regression model of the dependent variable y on independent variables x1, X2, X3, and x4: Using data with n 60 observations for each of the variables, a student obtains the following estimated regression equation for the model given: y0.35 0.58x1 + 0.45x2-0.25x3 - 0.10x4 He would like to conduct significance tests for a multiple regression relationship. He uses the F test to determine whether a significant relationship exists between the dependent variable and He uses the t...
4. A researcher built a model to predict an indicator of fitness using heart-rate (X1), weight (X2), height (X3) and age (X4) as predictors. The model was Y = 4 - 1.2 X1 -0.5 X2 +0.6 X3-0.2X4. The standard errors for X1, X2, X3, and X4 were 0.4, 0.3, 0.5, and 0.06 respectively. 1. If SSR=15500, R2 is 0.333 and F-stat is 5, complete the ANOVA table. 2. Which of these variables is statistically the most significant? Why?
Additional Problem A researcher collected data on Y and four X-variables: X1, X2, X3, X4, and he wants to obtain a regression model. However, he is not sure if all the four X-variables should be included in the model. He provides you with the information shown below, namely, the SSR obtained when Y was regressed on each subset of X-variables. Also given: SST-100, and that the sample size is n 12. Your task Apply the Forward-Stepwise selection method, with a-to-enter-...
ek-tin
Based on the following regression output, what proportion the total variation in Y is explained by X? Regression Statistics Multiple R 0.917214 R Square 0.841282 Adjusted R Square 0.821442 Standard Error 9.385572 Observations 10 ANOVA di SS MS Significance F 1 Regression 3735.3060 3735.30600 42.40379 0.000186 Residual 8 704.7117 88.08896 9 Total 4440.0170 Coefficients Standard Error t Stat P-value Lower 95% Intercept 31.623780 10.442970 3.028236 0.016353 7.542233 X Variable 1.131661 0.173786 6.511819 0.000186 0.730910 o a. 0.917214 o b.9.385572...
question #1 A-D. Please show work.
Q1. The following Regression function has been developed to check the relationship between the dependent variable y and the independent variable x1. Consider the following Minitab output and answer the questions. Regression Equation 9 = 0.86 + 0.65 x1 a) (4pt). Please fill out the Coefficients table appropriately. Coefficients Term Coef SE Coef T-Value P-Value VIF Constant (1) 1.38 16.58 0.000 X1 (ii) 0.231 7.00 0.000 1.00 b) (4pt). Please fill out the ANOVA...
4. Testing for significance Aa Aa Consider a multiple regression model of the dependent variable y on independent variables x1, x2, X3, and x4: Using data with n = 60 observations for each of the variables, a student obtains the following estimated regression equation for the model given: 0.04 + 0.28X1 + 0.84X2-0.06x3 + 0.14x4 y She would like to conduct significance tests for a multiple regression relationship. She uses the F test to determine whether a significant relationship exists...
Consider a multiple regression model of the dependent variable y on independent variables x1, X2, X3, and x4: Using data with n 60 observations for each of the variables, a student obtains the following estimated regression equation for the model given: y0.35 0.58x1 + 0.45x2-0.25x3 - 0.10x4 He would like to conduct significance tests for a multiple regression relationship. He uses the F test to determine whether a significant relationship exists between the dependent variable and He uses the t...
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