Solution-A:
sample size,n=dftotal+1=29+1=30
Solution-B:
y^=68.33+0.85x1-0.33x2-0.81x3-0.58x4
coefficient of x2=-0.33
Holding x1,x3 constant,for unit increase in x1,y decreases by 0.33 on an average
Solution-c:
Rsq=1-SS reg/SS total
=1-(227.09/380.16)
=0.4026463
=0.4026463*100
=40.26% variation in y is explained by model
Expalined variance by model=40.26%
Solution-d:
Ho:beta1=beta2=beta3=0
Ha:Atleast one of the beta is not =0
alpha=0.01
F=MS regression/MS total
=56.8/6.1
=9.311475
p value in excel
=F.DIST.RT(9.311475,4,25)
=9.46761E-05
=0.0000946
p<0.01
Reject Ho
Accept Ha
There is suffcient statistical evidence at 1% level of signiifcance to conclude that there is a linear relatiosnhip between y and indpendent variables
Overall regression model is signifcant
we can use this model for predicting from x1,x2 ,x3 and x4
(4) A regression software output is given below. df ANOVA Source Regression Residual Total 4 SS...
Click Submit to complete this assessment. Question 16 Given the following Regression Analysis Output ANOVA SS MS 903.19 301.06 52.72 1.62-8 1.37 5.7 16 19 Standard: tStat Nalue : Lower 95% Upper 95% 1992 132 0316E-08 15.853 23.977 0900.09 10.26 1.93E-08 07141085 0.1S 003 400.000162 087 0221 067 1215S 0590111 32411.906 ; 10.39 intercept x1 Conducting an individual test of hypothesis on each of the independent variables, you would consider dropping the independent variables A.XT and x3 8 x2 О.X3...
4. The following is the output of linear regression analysis, which includes dummy variables and interactions. The following are the variables: Y = Birth weights of infants born in preterm in three hospitals (A, B and C) X = Gestation age in weeks flif infant was born in Hospital A 10 Otherwise s X2= flif infant was born in Hospital B 10 Otherwise Variable Coefficient Standard deviation 1 P (approximate) Constant -1.1361 4904 .07648 01523 .7433 .6388 X -.8239 .6298...
given the following anova table: source DF SS MS F Regression 1 1,050.0 1,050.0 28.00 error 14 525.0 37.50 total 15 1,575.0 A. determine the coefficient of determination B. assuming a direct relationship between the variables, what is the correlation coefficient? C. determine the standard error of estimate
Given the following ANOVA table: Source DF SS MS F Regression 1 1,050 1,050.00 24.00 Error 12 525 43.75 Total 13 1,575 a. Determine the coefficient of determination.(Round your answer to 2 decimal places.) Coefficient of determination _____ b. Assuming a direct relationship between the variables, what is the correlation coefficient? (Round your answer to 2 decimal places.) Coefficient of correlation _____ c. Determine the standard error of estimate. (Round your answer to 2 decimal places.) Standard error of estimate...
Given the following ANOVA table: Source DF SS MS F Regression 1 1,500.0 1,500.00 24.00 Error 12 750.0 62.50 Total 13 2,250.0 Determine the coefficient of determination. (Round your answer to 3 decimal places.) Assuming a direct relationship between the variables, what is the correlation coefficient? (Round your answer to 2 decimal places.) Determine the standard error of estimate. (Round your answer to 2 decimal places.)
Given the following ANOVA table: Source DF SS MS F Regression 1 1,190.0 1,190.00 38.90 Error 17 520.0 30.59 Total 18 1,950.0 Determine the coefficient of determination. (Round your answer to 3 decimal places.) Assuming a direct relationship between the variables, what is the correlation coefficient? (Round your answer to 2 decimal places.) Determine the standard error of estimate. (Round your answer to 2 decimal places.)
Given the following ANOVA table: Source Regression Error Total F 24.00 DF 1 12 13 SS 1,050.0 525.0 1,575.0 MS 1,050.00 43.75 a. Determine the coefficient of determination. (Round your answer to 3 decimal places.) Coefficient of determination c. Determine the standard error of estimate. (Round your answer to 2 decimal places.) Standard error of estimate
3. The following is a regression output for estimated visitors to Raging Waters, a water amusement park. Coefficients Error t Stat P-value 45.61 1.99 -2.38 Intercept Temperature Ticket Price 84.998 2.391 0.4086 1.863 1.200 0.000 0.051 0.020 ANOVA MS 38.954 9.414 77.907 583.693 661.600 4.14 0.021 Residual Total 62 64 Write the regression equation. a. b. Conduct a global test of hypothesis (F-test) to see if any of the regression coefficients could be different from zero at the 5% significance...
The following regression output was obtained from a study of architectural firms. The dependent variable is the total amount of fees in millions of dollars. Predictor Coefficient SE Coefficient t p-value Constant 7.987 2.967 2.690 0.010 x1 0.122 0.031 3.920 0.000 x2 − 1.120 0.053 − 2.270 0.028 x3 − 0.063 0.039 − 1.610 0.114 x4 0.523 0.142 3.690 0.001 x5 − 0.065 0.040 − 1.620 0.112 Analysis of Variance Source DF SS MS F p-value Regression 5 371000 742...
The following regression output was obtained from a study of architectural firms. The dependent variable is the total amount of fees in millions of dollars. Predictor Coefficient SE Coefficient t p-value Constant 9.048 3.135 2.886 0.010 x1 0.284 0.111 2.559 0.000 x2 − 1.116 0.581 − 1.921 0.028 x3 − 0.194 0.189 − 1.026 0.114 x4 0.583 0.336 1.735 0.001 x5 − 0.025 0.026 − 0.962 0.112 Analysis of Variance Source DF SS MS F p-value Regression 5 1,895.93 379.2...