For Questions 4-11, use the swiss dataset, which is built into R.
Fit a multiple linear regression model with Fertility as the response and the remaining variables as predictors. You should use ?swiss to learn about the background of this dataset.
The following R code can be used to obtain the required results.
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##question 9 : F statistic value
> summary(lm(Fertility~.,data=swiss))$fstatistic[1] value 19.76106
##question 10 : Carry out the significance of the regression test at 0.01 level of significance
# as we can see the p - value of the F - Statistic is 5.594*10-10 which is less than 0.01> Thus our decision is that the regression model is significant,
## Question 11 : F-statistic value and p-value for the new model
# as you may notice the f-statistic value is 28.14 and the p-value of the test for regression significance is 3.15*10-10
For Questions 4-11, use the swiss dataset, which is built into R. Fit a multiple linear regression model with Fertility...
all data is built in in R 4. For Questions 4-11, use the swiss dataset, which is built into R. Fit a multiple linear regression model with Fertility as the response and the remaining variables as predictors. You should use ?swiss to learn about the background of this dataset 1 Run Reset Use your fitted model to make a prediction for a Swiss province in 1888 with: 54% of males involved in agriculture as occupation 23% of draftees receiving highest...
For Questions 4-11, use the swiss dataset, which is built into R. Fit a multiple linear regression model with Fertility as the response and the remaining variables as predictors. You should use ?swiss to learn about the background of this dataset. 7. 1 Run Reset Create a 95% confidence interval for the average Fertility for a Swiss province in 1888 with: 40% of males involved in agriculture as occupation 28% of draftees receiving highest mark on army examination 10% of...
The following table is the output of multiple linear regression analysis. a. Use the table to report the F statistic. What is its degree of freedom? What is the number of observations. b. Find the p-value related to F on the computer output and report its value. Using the p-value, test the significance of the regression model at the .10, .05, .01, and .001 levels of significance. What do you conclude? Please show work and explain each step! df ANOVA...
31. Suppose you fit a multiple linear regression model y = β0 + β1x1 + β2x2 + β3x3 + β4x4 + ε to n = 30 data points and obtain SSE = 282 and R^2 = 0.8266 a.) Find an estimate of s^2 for the multiple regression model (a) s^2 ≈ 30.9856 (b) s^2 ≈ 28.6021 (c) s^2 ≈ 1.3111 (d) s^2 ≈ 29.7938 (d) b.) Based on the data information given in a.), you use F-test to test H0...
For this exercise we will run a regression using Swiss demographic data from around 1888. The sample is a cross-section of French speaking counties in Switzerland This data come with the R package datasets. The first step is to load the package into your current environment by typing the command libraryldatasets) in to the R console. This loads a number of datasets including one called swiss. Type help/swiss) in the console for additional details. The basic variable definitions are as...
Use the following ANOVA table for regression to answer the questions. Analysis of Variance Source DF SS MS F P Regression 1 3404.5 3404.5 22.3 0.000 Residual Error 174 26569.8 152.7 Total 175 29974.3 Give the F-statistic and p-value. Enter the exact answers. The F-statistic is ? The p-value is ? Choose the conclusion of this test using a 5% significance level. Reject H0. The model is effective. Do not reject H0. We did not find evidence that the model...
Use the following ANOVA table for regression to answer the questions. Analysis of Variance Source DF SS MS F P Regression 1 289.0 289.0 2.01 0.158 Residual Error 174 25021.2 143.8 Total 175 25310.2 Give the F-statistic and p-value. Enter the exact answers. The F-statistic is . The p-value is Choose the conclusion of this test using a 5% significance level. Do not reject H0. We did not find evidence that the model is effective. Reject H0. The model is...
11. (25 points) A multiple regression analysis is conducted to determine factors that relate to the success of sales associates. The regression is conducted between annual sales (Y in $1,000s), years of experience gion (X3; zero representing USA and 1 representing Canada) was performed on a sample of 29 people, and the following results were obtamed where SSR 84 60 amd SSE 57.5. Standard Coefficient Error Constant X1 X2 X3 40.28 1.36 12.03 1.65 0.121.22 6.481.54 Write the regression equation....
3. The table below shows the regression output of a multiple regression model relating the beginning salaries of employees in a given company to the following independent variables: Sex : an indicator variable (1=man and 0-woman) ducation years of schooling at the time of hire Experience number of months of previous work experience Source Regression Residual Total Df 4 8822,387,82 254,407 92 MS F-value 23.763,297 5,940,82423.35 46,151,118 Coefficient table Variable Constant Sex Education Experience Months t-value 10.94 6.02 3.22 2.16...