Homework Answers
As given plot we see that all points are lies in straight line so it gives idea that the model is good fit .Also we see from the residual by predicted plot is randomly dispersed . Therefore given model is good fit. There is no lack of fit.
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looking at the "Actual by predicted" and " Residual by predicted"
plots
b. For the model...
Discuss the Actual by Predicted Plot and Residual Plot. Discuss any issues that you find with...
Discuss the Actual by Predicted Plot and Residual Plot.
Discuss any issues that you find with either the model adequacy or
possible data issues such as outliers and influence.
Actual by Predicted Plot Y Actual 0 80 10 20 30 40 50 60 70 Y Predicted RMSE=10.903 RSq=0.71 PValue=0.0008 Residual by Predicted Plot Y Residual 0 10 20 30 40 Y Predicted 50 60 70 80
Discuss the actual by predidected plot and the Residual plot. Discuss any issues that you find...
Discuss the actual by predidected plot and the Residual plot.
Discuss any issues that you find with either the model adequacy or
possible data issues such as outliers and influence.
4 Actual by Predicted Plot Y Actual 0 80 10 20 30 40 50 60 70 Y Predicted RMSE=10.615 RSq=0.73 PValue=0.0003 Residual by Predicted Plot Y Residual 0 10 20 30 40 Y Predicted 50 60 70 80
A) 380 370 360 350 01/1985 01/1987 01/1989 01/1991 01/1993 01/1995 01/1997 01/1999 01/2001 01/2003 date...
A) 380 370 360 350 01/1985 01/1987 01/1989 01/1991 01/1993 01/1995 01/1997 01/1999 01/2001 01/2003 date B) 15 10 10 15 01/1985 01/1989 01/1993 01/1997 01/2001 01/2005 date C) 2- 2- 01/1985 01/1989 01/1991 01/1993 01/1995 01/1997 01/1999 01/2001 01/2003 date D) 01/1985 01/1987 01/1989 01/1991 01/1993 01/1995 01/1997 01/1999 01/2001 01/2003 01/2005 Atmospheric Carbon Dioxide Record from Alert, Canada. The time series plot in Figure A displays Monthly Carbon dioxide (CO2) measurements at Alert, NWT, Canada from July 1985...
2. [20| Consider the car stopping distance example we studied in Section 2.2, with the model...
2. [20| Consider the car stopping distance example we studied in Section 2.2, with the model 2 where d is the stopping distance, v is the velocity of the car before braking, tr is the response time, and k is a coefficient related to the ratio of the braking force and the mass fo the car. (a) [5] Fit the model (i.e, determine the parameters t and k) to the data in the first column and the last column of...
QUESTION 19 For the following software output, check each assumption/condition to run linear regression and state...
QUESTION 19 For the following software output, check each assumption/condition to run linear regression and state whether it is appropriate to use linear regression. Bivariate Fit of pluto By alpha 20 15 10 5 0 e 0.05 0.15 C 0.1 alpha Linear Fit Linear Fit pluto -0.597417 16543195*alpha Summary of Fit RSquare RSquare Adj Root Mean Square Error Mean of Response Observations (or Sum Wgts) 0.915999 0.911999 2.172963 6.73913 23 Analysis of Variance Sum of DF Squares Mean Square Source...
Please answer asap, thanks! We collect the following data to study the operation of a plant for the oxidation of ammonia to nitric acid. In the regression models, x is air flow, x2 is cooling w...
Please answer asap, thanks!
We collect the following data to study the operation of a plant for the oxidation of ammonia to nitric acid. In the regression models, x is air flow, x2 is cooling water inlet temperature and y is stack loss. The standard errors of predicted are derived from the second model. Note that 1 57.765 and Σ(x1,-%)2-871.06. StdErr Pred y 27 0.9980645052 2 0.3599917876 23 0.4203293994 24 0.5286438199 4 0.5286438199 23 0.5199911743 8 0.5148291582 8 0.5148291582 7...
a. Find the quartic equation describing the model. Round to three decimal places. b. Complete the...
a. Find the quartic equation describing the model. Round to
three decimal places.
b. Complete the table provided with the predicted oil imports
from OPEC, and the error. Use the unrounded model.
c. Find the average error for the model. Use the unrounded
model.
d. The scatter plot of the data is shown. Sketch the graph of
the model showing how it relates to the scatter plot.
e. Using the unrounded model, what would be the predicted oil
imports from...
A study was conducted in which participants looked at photographs of various people and guessed how...
A study was conducted in which participants looked at photographs of various people and guessed how old each phot regression analy ographed person was. Then the amount of error in each guess was calculated, and this was used as a response variable in Here are the names of the variables used: these will be referenced in the questions below: 2. Difference between guessed age and true age (Positive errors are overestimates, i.e. guessing an age greater than true age; negative...
its 8.17 the one that is highlighted and I have also attached the models. Xi2: 0 1 0 a. Explain how each regression coefficient in model (8.33) is interpreted hene. b. Fit the regression model...
its 8.17 the one that is highlighted and I have also
attached the models.
Xi2: 0 1 0 a. Explain how each regression coefficient in model (8.33) is interpreted hene. b. Fit the regression model and state the estimated regression function. c. Test whether the X2 variable can be dropped from the regression model; use α 01 St ate the alternatives, decision rule, and conclusion. d. Obtain the residuals for regression model (8.33) and plot them against XiXz. Is there...
:2. A study was conducted in which participants looked at photographs of various people and guessed how old each photographed person was. Then the amount of error in each guess was calculated, and th...
:2. A study was conducted in which participants looked at photographs of various people and guessed how old each photographed person was. Then the amount of error in each guess was calculated, and this was used as a response variable in regression analyses. Here are the names of the variables used; these will be referenced in the questions below: Error: Difference between guessed age and true age. (Positive errors are overestimates, i.e. guessing an age greater than true age; negative...
Discuss the Actual by Predicted Plot and Residual Plot.
Discuss any issues that you find with either the model adequacy or
possible data issues such as outliers and influence.
Actual by Predicted Plot Y Actual 0 80 10 20 30 40 50 60 70 Y Predicted RMSE=10.903 RSq=0.71 PValue=0.0008 Residual by Predicted Plot Y Residual 0 10 20 30 40 Y Predicted 50 60 70 80
Discuss the actual by predidected plot and the Residual plot.
Discuss any issues that you find with either the model adequacy or
possible data issues such as outliers and influence.
4 Actual by Predicted Plot Y Actual 0 80 10 20 30 40 50 60 70 Y Predicted RMSE=10.615 RSq=0.73 PValue=0.0003 Residual by Predicted Plot Y Residual 0 10 20 30 40 Y Predicted 50 60 70 80
A) 380 370 360 350 01/1985 01/1987 01/1989 01/1991 01/1993 01/1995 01/1997 01/1999 01/2001 01/2003 date B) 15 10 10 15 01/1985 01/1989 01/1993 01/1997 01/2001 01/2005 date C) 2- 2- 01/1985 01/1989 01/1991 01/1993 01/1995 01/1997 01/1999 01/2001 01/2003 date D) 01/1985 01/1987 01/1989 01/1991 01/1993 01/1995 01/1997 01/1999 01/2001 01/2003 01/2005 Atmospheric Carbon Dioxide Record from Alert, Canada. The time series plot in Figure A displays Monthly Carbon dioxide (CO2) measurements at Alert, NWT, Canada from July 1985...
2. [20| Consider the car stopping distance example we studied in Section 2.2, with the model 2 where d is the stopping distance, v is the velocity of the car before braking, tr is the response time, and k is a coefficient related to the ratio of the braking force and the mass fo the car. (a) [5] Fit the model (i.e, determine the parameters t and k) to the data in the first column and the last column of...
QUESTION 19 For the following software output, check each assumption/condition to run linear regression and state whether it is appropriate to use linear regression. Bivariate Fit of pluto By alpha 20 15 10 5 0 e 0.05 0.15 C 0.1 alpha Linear Fit Linear Fit pluto -0.597417 16543195*alpha Summary of Fit RSquare RSquare Adj Root Mean Square Error Mean of Response Observations (or Sum Wgts) 0.915999 0.911999 2.172963 6.73913 23 Analysis of Variance Sum of DF Squares Mean Square Source...
Please answer asap, thanks!
We collect the following data to study the operation of a plant for the oxidation of ammonia to nitric acid. In the regression models, x is air flow, x2 is cooling water inlet temperature and y is stack loss. The standard errors of predicted are derived from the second model. Note that 1 57.765 and Σ(x1,-%)2-871.06. StdErr Pred y 27 0.9980645052 2 0.3599917876 23 0.4203293994 24 0.5286438199 4 0.5286438199 23 0.5199911743 8 0.5148291582 8 0.5148291582 7...
a. Find the quartic equation describing the model. Round to
three decimal places.
b. Complete the table provided with the predicted oil imports
from OPEC, and the error. Use the unrounded model.
c. Find the average error for the model. Use the unrounded
model.
d. The scatter plot of the data is shown. Sketch the graph of
the model showing how it relates to the scatter plot.
e. Using the unrounded model, what would be the predicted oil
imports from...
A study was conducted in which participants looked at photographs of various people and guessed how old each phot regression analy ographed person was. Then the amount of error in each guess was calculated, and this was used as a response variable in Here are the names of the variables used: these will be referenced in the questions below: 2. Difference between guessed age and true age (Positive errors are overestimates, i.e. guessing an age greater than true age; negative...
its 8.17 the one that is highlighted and I have also
attached the models.
Xi2: 0 1 0 a. Explain how each regression coefficient in model (8.33) is interpreted hene. b. Fit the regression model and state the estimated regression function. c. Test whether the X2 variable can be dropped from the regression model; use α 01 St ate the alternatives, decision rule, and conclusion. d. Obtain the residuals for regression model (8.33) and plot them against XiXz. Is there...
:2. A study was conducted in which participants looked at photographs of various people and guessed how old each photographed person was. Then the amount of error in each guess was calculated, and this was used as a response variable in regression analyses. Here are the names of the variables used; these will be referenced in the questions below: Error: Difference between guessed age and true age. (Positive errors are overestimates, i.e. guessing an age greater than true age; negative...
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