Based on the below data what will be the value of SST?
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Please no written by hand solution
Based on the below data what will be the value of SST?
| Regression Statistics | ||||
| Multiple R | ||||
| R Square | ||||
| Adjusted R Square | ||||
| Standard Error | ||||
| Observations | 8 | |||
| ANOVA | ||||
| df | SS | MS | F | |
| Regression | 1 | 20 | 20 | 20 |
| Residual | 6 | 11 | 1 | |
| Total | 7 | |||
| Coefficients | Standard Error | t Stat | P-value | |
| Intercept | -1 | 31.274666 | 3.984284 | 0.007248 |
| Advertising (thousands of $) | 37 | 6.19330674 | 1.610802 | 0.158349 |
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- Use the following ANOVA table for regression to answer the questions. Response: Y Source DF Sum Sq Mean Sq F-value Pr(>F) Regression 1 10.782 10.782 2.32 0.129 Residual Error 342 1589.274 4.647 Total 343 1600.056 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%5% significance level. A) Do not reject H0H0. We did not find evidence that the model is effective. B) Do not reject H0H0. We did not find evidence that the model is not effective. C) Reject H0H0. The model is effective. D) Reject H0H0. The model is not effective.A regression analysis was performed and the summary output is shown below. Regression Statistics Multiple R 0.7193267530.719326753 R Square 0.5174309770.517430977 Adjusted R Square 0.4991055710.499105571 Standard Error 8.6995238488.699523848 Observations 165165 ANOVA dfdf SSSS MSMS F� Significance F� Regression 66 12,821.56512,821.565 2136.9282136.928 28.235728.2357 8.9037E-238.9037E-23 Residual 158158 11,957.71111,957.711 75.68275.682 Total 164164 24,779.27624,779.276 Step 1 of 2 : How many independent variables are included in the regression modelUse the following ANOVA table for regression to answer the questions. Response: Y Source DF Sum Sq Mean Sq F-value Pr(>F) Regression 1 10.964 10.964 3.02 0.083 Residual Error 342 1241.460 3.630 Total 343 1252.424 Give the F-statistic and p-value.Enter the exact answers.The F-statistic is Enter your answer; F-statistic .The p-value is Enter your answer; p-value . Choose the conclusion of this test using a 5% significance level. Reject H0. The model is not effective. Do not reject H0. We did not find evidence that the model is not effective. Reject H0. The model is effective. Do not reject H0. We did not find evidence that the model is effective.
- Use the following ANOVA table for regression to answer the questions. Response: Y Source DF Sum Sq Mean Sq F-value Pr(>F) Regression 1 351.47 351.47 13.32 0.000 Residual Error 359 9474.01 26.39 Total 360 9825.48 Give the F-statistic and p-value.Enter the exact answers.The F-statistic is .The p-value is .Define how to use t-Statistic in Regression When the Sample Size Is Small? Explain Use of the Student t Distribution in Practice?Use the following ANOVA table for regression to answer the questions. Response: Y Source DF Sum Sq Mean Sq F-value Pr(>F) Regression 1 343.82 343.82 13.80 0.000 Residual Error 359 8942.69 24.91 Total 360 9286.51 Give the F-statistic and p-value.Enter the exact answers.The F-statistic is Enter your answer; F-statistic .The p-value is Enter your answer; p-value
- It appears that there is a significant relationship between cyberbullying (X) and internet trolling (Y). Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .889a .790 .748 1.50555 a. Predictors: (Constant), CyberBullying ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 42.667 1 42.667 18.824 .007b Residual 11.333 5 2.267 Total 54.000 6 a. Dependent Variable: InternetTrolling b. Predictors: (Constant), CyberBullying Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) .333 1.639 .203 .847 CyberBullying 1.333 .307 .889 4.339 .007 a. Dependent Variable: InternetTrolling State hypothesis for the correlation: Is the correlation significant using α = .05? State the conclusion in APA format.…Use the following ANOVA table for regression to answer the questions. Response: Y Source DF Sum Sq Mean Sq F-value Pr(>F) Regression 1 10.549 10.549 2.32 0.129 Residual Error 342 1555.074 4.547 Total 343 1565.623 Give the F-statistic and p-value.Enter the exact answers.The F-statistic is .The p-value is . SHOW HINT LINK TO TEXT Choose the conclusion of this test using a 5% significance level. Reject H0. The model is effective. Reject H0. The model is not effective. Do not reject H0. We did not find evidence that the model is not effective. Do not reject H0. We did not find evidence that the model is effective.Use the following ANOVA table for regression to answer the questions. Response: Y Source DF Sum Sq Mean Sq F-value Pr(>F) Regression 1 351.43 351.43 11.64 0.001 Residual Error 359 10838.21 30.19 Total 360 11189.64 Give the F-statistic and p-value.Enter the exact answers.The F-statistic is .The p-value is . SHOW HINT LINK TO TEXT 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 is not effective. Do not reject H0. We did not find evidence that the model is effective. Reject H0. The model is not effective.
- Analyse the following regression Regression Statistics Multiple R 0.79716916 R Square 0.63547867 Adjusted R Square 0.63254686 Standard Error 198.375358 Observations 377 ANOVA df SS MS F Significance F Regression 3 25589530 8529843.34 216.753245 2.2501E-81 Residual 373 14678587.9 39352.7826 Total 376 40268117.9 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -97.981174 79.2847437 -1.2358137 0.21730553 -253.88228 57.9199296 -253.88228 57.9199296 EquivArea 3.5523258 0.15149067 23.4491399 2.2549E-75 3.254443 3.85020861 3.254443 3.85020861 Years 2.04629486 0.31770115 6.44094253 3.6636E-10 1.42158501 2.67100471 1.42158501 2.67100471 Condition 15.0379067 10.2144479 1.47221924 0.14180492 -5.0472147 35.1230282 -5.0472147 35.1230282A regression analysis was performed and the summary output is shown below. Regression Statistics Multiple R 0.7802268560.780226856 R Square 0.6087539470.608753947 Adjusted R Square 0.5870180550.587018055 Standard Error 6.7217061336.721706133 Observations 20 ANOVA dfdf SSSS MSMS F� Significance F� Regression 11 1265.3871265.387 1265.3871265.387 28.006928.0069 4.9549E-054.9549E-05 Residual 1818 813.264813.264 45.18145.181 Total 1919 2078.6512078.651 Step 2 of 2: Which measure is appropriate for determining the proportion of variation in the dependent variable explained by the set of independent variable(s) in this model?A company manufactures printers and fax machines at plants located in Atlanta, Dallas, and Seattle. To measure how much employees at these plants know about quality management, a random sample of 6 employees was selected from each plant and the employees selected were given a quality awareness examination. The examination scores for these 18 employees are shown in the following table. The sample means, sample variances, and sample standard deviations for each group are also provided. Managers want to use these data to test the hypothesis that the mean examination score is the same for all three plants. Sample mean Sample variance Sample standard deviation Plant 1 Atlanta 84 76 81 76 70 81 78 25.2 5.02 Plant 2 Plant 3 Dallas Seattle 72 74 72 74 70 88 75 42.8 6.54 60 64 62 68 76 66 66 32.0 5.66
