Question

In: Statistics and Probability

The accompanying data resulted from a study of the relationship between y = brightness of finished...

The accompanying data resulted from a study of the relationship between y = brightness of finished paper and the independent variables

x1 = hydrogen peroxide (% by weight), x2 = sodium hydroxide (% by weight), x3 = silicate (% by weight), and x4 = process temperature.

x1 x2 x3 x4 y
0.2 0.2 1.5 145 83.9
0.4 0.2 1.5 145 84.9
0.2 0.4 1.5 145 83.4
0.4 0.4 1.5 145 84.2
0.2 0.2 3.5 145 83.8
0.4 0.2 3.5 145 84.7
0.2 0.4 3.5 145 84.0
0.4 0.4 3.5 145 84.8
0.2 0.2 1.5 175 84.5
0.4 0.2 1.5 175 86.0
0.2 0.4 1.5 175 82.6
0.4 0.4 1.5 175 85.1
0.2 0.2 3.5 175 84.5
0.4 0.2 3.5 175 86.0
0.2 0.4 3.5 175 84.0
0.4 0.4 3.5 175 85.4
x1 x2 x3 x4 y
0.1 0.3 2.5 160 82.9
0.5 0.3 2.5 160 85.5
0.3 0.1 2.5 160 85.2
0.3 0.5 2.5 160 84.5
0.3 0.3 0.5 160 84.7
0.3 0.3 4.5 160 85.0
0.3 0.3 2.5 130 84.9
0.3 0.3 2.5 190 84.0
0.3 0.3 2.5 160 84.5
0.3 0.3 2.5 160 84.7
0.3 0.3 2.5 160 84.6
0.3 0.3 2.5 160 84.9
0.3 0.3 2.5 160 84.9
0.3 0.3 2.5 160 84.5
0.3 0.3 2.5 160 84.6

(a) Find the estimated regression equation for the model that includes all independent variables, all quadratic terms, and all interaction terms. (Round your answers to four decimal places.)

= ____ + _____ x1 + ____ x2 + ____ x3 + ____ x4 + _____ x12 + _____ x22 + ______ x32 + _____ x42 + ______ x1x2 + _____ x1x3 + _____ x1x4 + _____ x2x3 + ______ x2x4 + ______ x3x4

(b) Calculate SSResid. (Round your answer to four decimal places.)

SSResid =  

Solutions

Expert Solution

using excel>data>data analysis>Regression

we have

SUMMARY OUTPUT
Regression Statistics
Multiple R 0.940495
R Square 0.884531
Adjusted R Square 0.783496
Standard Error 0.3529
Observations 31
ANOVA
df SS MS F Significance F
Regression 14 15.26416 1.090297 8.754683 4.97E-05
Residual 16 1.992619 0.124539
Total 30 17.25677
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept 76.43709 9.081796 8.416517 2.85E-07 57.18454 95.68963 57.18454 95.68963
x1 -7.34524 10.79946 -0.68015 0.506133 -30.2391 15.5486 -30.2391 15.5486
x2 9.613095 10.79946 0.890146 0.386577 -13.2807 32.50693 -13.2807 32.50693
x3 -0.91488 1.067606 -0.85695 0.404128 -3.1781 1.348342 -3.1781 1.348342
x4 0.096323 0.098342 0.979465 0.341929 -0.11215 0.304799 -0.11215 0.304799
X12 -13.4524 6.599354 -2.03844 0.058386 -27.4424 0.537625 -27.4424 0.537625
X22 2.797619 6.599354 0.423923 0.677266 -11.1924 16.78763 -11.1924 16.78763
X32 0.027976 0.065994 0.423923 0.677266 -0.11192 0.167876 -0.11192 0.167876
X42 -0.00032 0.000293 -1.09138 0.29127 -0.00094 0.000302 -0.00094 0.000302
X1X2 3.75 8.82251 0.425049 0.676462 -14.9529 22.45289 -14.9529 22.45289
X1X3 -0.75 0.882251 -0.8501 0.407812 -2.62029 1.120289 -2.62029 1.120289
X1X4 0.141667 0.058817 2.408612 0.028428 0.016981 0.266353 0.016981 0.266353
X2X3 2 0.882251 2.266929 0.037608 0.129711 3.870289 0.129711 3.870289
X2X4 -0.125 0.058817 -2.12525 0.049491 -0.24969 -0.00031 -0.24969 -0.00031
X3X4 0.003333 0.005882 0.566732 0.57876 -0.00914 0.015802 -0.00914 0.015802

a) the estimated regression equation for the model that includes all independent variables, all quadratic terms, and all interaction terms is

= 76.4371 -7.3452 x1 + 9.6131 x2 -0.9149 x3 +0.0963 x4 -13.4524 x12 +2.7976 x22 +0.0280 x32 -0.0003 x42 + 3.7500 x1x2 -0.7500 x1x3 + 0.1416 x1x4 + 2.000 x2x3 -0.1250 x2x4 +0.0033 x3x4

(b)

SSResid =  1.9926


Related Solutions

The data in the accompanying table is from a paper. Suppose that the data resulted from...
The data in the accompanying table is from a paper. Suppose that the data resulted from classifying each person in a random sample of 45 male students and each person in a random sample of 92 female students at a particular college according to their response to a question about whether they usually eat three meals a day or rarely eat three meals a day. Usually Eat 3 Meals a Day Rarely Eat 3 Meals a Day Male 25 20...
The following data were obtained in a study of the relationship between diastolic blood pressure (Y)...
The following data were obtained in a study of the relationship between diastolic blood pressure (Y) and age (X) for boys 5 to 13 years old. X 5 8 11 7 13 12 12 6 Y 63 67 74 64 75 69 90 60 Fit a simple linear regression model to the data and plot the residuals against the fitted values. Omit case 7 and refit the model. Plot the residuals versus the fitted values and compare to what you...
Consider the following data from a study of the relationship between smoking status of the mother...
Consider the following data from a study of the relationship between smoking status of the mother and infant birth weight. Select the appropriate non-parametric test for data analysis and show the steps of hypothesis testing (α = 0.05).   Non-smokers Ex-smokers Smoker (< ½ pack per day) Smoker (≥ ½ pack per day) 8.56 7.39 5.97 7.03 8.47 8.64 6.77 5.24 6.39 8.54 7.26 6.14 9.26 5.37 5.74 6.74 7.98 9.21 8.74 6.62 6.84 6.30 7.37 4.94 6.34 Step 1: State...
Q12: The following data are from a study of the relationship between average consumption of saturated...
Q12: The following data are from a study of the relationship between average consumption of saturated fat (in grams) and cholesterol level (in milligram per hundred milliliters) of eight males: Subject 1 2 3 4 5 6 7 8 Fat consumption (x) 55 65 50 34 43 58 72 36 Cholesterol level (y) 180 215 195 165 170 204 235 150 Below are some of the summaries of this data: ∑?=413, ∑?=1514, ????=1277.875, ????=5591.5 and ????=2536.75 (a) Compute the estimates...
Data from a study investigating the relationship between smoking and aortic stenosis, a narrowing or stricture...
Data from a study investigating the relationship between smoking and aortic stenosis, a narrowing or stricture of the aorta that impedes the flow of blood to the body are available below. It is known that gender is associated with both of these variables and it is suspected that it might influence the observed relationship between them. Smoking status is saved under the variable name SMOKE, the presence of aortic stenosis under the name DISEASE, and gender under the name SEX....
Regression methods were used to analyze the data from a study investigating the relationship between roadway...
Regression methods were used to analyze the data from a study investigating the relationship between roadway surface temperature (x) and pavement deflection (y). Summary quantities were n = 20, ∑?! = 12.75, ∑?!" = 8.86, ∑?! = 1478, ∑?!" = 143215.8, ∑?!?! = 1083.67. Give a 95% confidence interval for the mean response of pavement deflection given that temperature is 90 F.
The following data was collected during a study to determine if there is a relationship between...
The following data was collected during a study to determine if there is a relationship between the vertical drop of the mountain and the number of trails at the resort in New York State. (1200, 30), (700, 50), (700, 24), (1500, 62), (1010, 23), (3350, 67), (400, 15), (1600, 34) a.) Generate the regression equation. b.) Determine the correlation coefficient. c.) Is there enough evidence to conclude that the slope of the regression line is not zero at the 98%...
14. A study has shown that a good model for the relationship between X and Y...
14. A study has shown that a good model for the relationship between X and Y , the first and second year batting averages of a randomly chosen major league baseball player, is given by the equation Y = .159 + .4X + e, where e is a normal random variable with mean 0. That is, the model is a simple linear regression with a regression toward the mean. (a) If a player’s batting average is .200 in his first...
A study investigating the relationship between blood pressure rise in millimetre of mercury (y) and the...
A study investigating the relationship between blood pressure rise in millimetre of mercury (y) and the sound pressure level in decibels (x). Use the correlation and regression technique to investigate the relationship between the variables. x 1 0 1 2 5 1 4 6 y 60 63 65 70 70 70 80 90
This sample data was collected to study the relationship between the rent charged with the size...
This sample data was collected to study the relationship between the rent charged with the size of a dwelling. Identify the dependent variable and independent variable. Do they have a cause and effect relationship? Explain. Run Regression on this data. Make sure to check the boxes for charts, normal distribution, residual charts, etc. Write the null and alternate hypotheses to test if the linear relationship (slope) is significant or not. Conduct F test to determine if you are going to...
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT