Find the predicted value of the number of deaths for the meanvalues of the independent variables. I want to remind you that adummy variable is only 0 or 1.Regression 3:ANOVAdfSSMSFSignificance F20895730.8RegressionResidual36965243.6 214.49181994.82446E-27461493768.8832473.23652Total49 22389499.68StandardCoefficientsErrort StatP-value0.04542579Intercepttext bantotal miles driventotmilessquared132.0282137 64.198385572.056565949-211.3019126 54.88284694-3.850053786 0.0003630620.012343265 0.00113090410.9145082 2.34057E-14-6.95969E-09 3.95515E-09-1.759653201 0.045115874numberofdeaths text ban total_miles_driven urban_percent cell subscription cell banMean660.920.7056304.8635.825000.780.16Median478.5144116.4933.54250.5St. Dev.665.960.4965495.3218.706929.320.45Minimum494492.08618Maximum3378326271.6584366161657.0388

Answered: Find the predicted value of the number…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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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 10.964 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.
Chapter 9, Section 2, Exercise 030 Use the following ANOVA table for regression to answer the questions. Analysis of Variance Source DF SS MS F P Regression 1 304.5 304.5 2.01 0.158 Residual Error 174 26361.0 151.5 Total 175 26665.5 Give the F-statistic and p-value.Enter the exact answers.The F-statistic is=The p-value is=
A multiple regression analysis produced the following tables. Predictor Coefficients StandardErrort Statistic p-valueIntercept -139.609 2548.989 -0.05477 0.957154x 24.24619 22.25267 1.089586 0.295682x 32.10171 17.44559 1.840105 0.08869Source df SS MS F p-valueRegression 2 302689 151344.5 1.705942 0.219838Residual 13 1153309 88716.07Total 15 1455998Using = 0.01 to test the null hypothesis H :?1 = ?2 = 0, the critical F value is ____.6.701.964.845.995.70
Please answer the photo attached in excel, please provide the formula too. Thank you The lecture in the photo attached
Using the Excel output reported above, if we were to test to see whether "Attendance" is statistically significantly associated with "Score received on the exam," we would conclude that we should Regression Statistics Multiple R R Square Standard Error Observations Intercept Attendance 0.142620229 0.02034053 20.25979924 22 Coefficients Standard Error 39.39027309 37.24347659 0.340583573 0.52852452 T Stat 1.057642216 0.644404489 P-value 0.302826622 0.526635689 O Reject the null hypothesis and conclude that Attendance IS statistically significantly associated with "Score received on the exam" Reject the null hypothesis and conclude that Attendance is is NOT statistically significantly associated with "Score received on the exam" Accept the null hypothesis and conclude that Attendance IS statistically significantly associated with "Score received on the exam" Fail to reject the null hypothesis and conclude that we cannot say that Attendance is statistically significantly associated with…
Shown below is a portion of a computer output for regression analysis relating y (dependent variable) and x (independent variable). ANOVA df SS Regression 1 24.061 Residual 10 67.979 Coefficients Standard Error Intercept 11.064 2.049 x −0.566 0.301 (a) What has been the sample size for the above regression analysis? (b) Perform a t-test and determine whether or not x and y are related. Let ? = 0.05. State the null and alternative hypotheses. (Enter != for ≠ as needed.) H0: Ha: Find the value of the test statistic. (Round your answer to three decimal places.) Find the p-value. (Round your answer to four decimal places.) p-value = What is your conclusion? .
pls Answer No. 15
Based on the ANOVA table given, is there enough evidence at the 0.05 level of significance to conclude that the linear relationship between the independent variables and the dependent variable is statistically significant? Source df SS Regression 2 984.715358 Residual 7 298.884642 Total 9 1283.600000 ANOVA MS F 492.357679 11.531217 42.697806 Significance F 0.006092 Copy Data Ĵ Based on the ANOVA table given, is there enough evidence at the 0.05 level of significance to conclude that the linear relationship between the independent variables and the dependent variable is statistically significant? Source df SS Regression 2 984.715358 Residual 7 298.884642 Total 9 1283.600000 ANOVA MS F Significance F 492.357679 11.531217 0.006092 42.697806 Copy Data
The regional manager of a franchise business is interested in understanding how income in a region affects sales. Below is a regression output for sales ($’000) regressed on the average household income of an area ($’000) Linear Fit Sales = 14.5774 + 2.9048*Income Summary of Fit RSquare 0.9683 RSquare Adj 0.9630 Root Mean Square Error 3.1083 Mean of Response 43.6250 Analysis of Variance Source DF Sum of Squares Mean Square F Ratio Model 1 1771.9048 1771.90 183.3946 Error 6 57.9702 9.66 Pro>F C. Total 7 1829.8750 ItI Intercept 14.5774 2.4101 6.05 0.0009* Income 2.9098 0.2145 13.54 < 0.0001* Answer the following questions: (i) What is the average sales across all regions? (ii) Interpret the slope of regression (iii) What is the prediction of the value of sales in a region with an average…
A car dealership would like to develop a regression model that would predict the number of cars sold per month by a dealership employee based on theemployee's number of years of sales experience. The accompanying regression output was developed based on a random sample of employees. ANOVA df SS Regression 1 79.909407 Residual 23 261.210593 Total 24 341.12 Coefficients Standard Error Intercept 7.271539 1.229763 Slope 0.539854 0.203521 The coefficient of determination is 0.234 Test statistic= 0.704 P-value= 0.014 Construct a 95% confidence interval around the sample slope and interpret its meaning. The confidence interval is (__________,_________). (Type an integer or decimal rounded to three decimal places as needed.)
Only round final answer to 2 decimal places.

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