Model SummaryAdjusted RStd. Error of theModelRR SquareSquareEstimate1.91988764259ANOVAModelSum of SquaresdfMean SquareFSig1Regression11.718002ResidualTotal25.5007CoefficientsStandardizedUnstandardized CoefficientsCoefficients4ModelBStd. ErrorBetatSig.1(Constant)83.2301.57452.882000TVAdv.3041.1537.532001NewsAdv.321.6214.057010What is SSE?O.6051.065O-2.506O 2.605

R-squared (R²) is defined as the proportion of the variance in the dependent variable that is…

Answered: Model Summary Adjusted R Std. Error of…

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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Given the following regression output, Predictor Coefficient SE Coefficient t p-value Constant 84.998 1.863 45.62 0.000 x1 2.391 1.200 1.99 0.051 x2 -0.409 0.172 -2.38 0.021 Analysis of Variance Source DF SS MS F p-value Regression 2 77.907 38.954 4.138 0.021 Residual Error 62 583.693 9.414 Total 64 661.600 answer the following questions: e-1. State the decision rule for each independent variable. Use the 0.05 significance level. (Round your answers to 3 decimal places. Negative values should be indicated by a minus sign.) e-2. Compute the value of the test statistic. (Round your answers to 2 decimal places. Negative values should be indicated by a minus sign.) e-3. Which variable would you consider eliminating? Outline a strategy for deleting independent variables in this case.
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Analysis of Variance Source DF SS MS F P Regression 1 3390.0 3390.0 19.4 0.000 Residual Error 174 30397.8 174.7 Total 175 33787.8 Use the information in the table to give the sample size and to calculate R^2.Enter the exact answer for the sample size, and round R^2 to one decimal place.Enter your answer; n Enter your answer; R^2 %
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? ANOVA Source df MS F Significance F Regression 3 406.124504 135.374835 0.849953 0.497712 Residual 10 1592.732639 159.273264 Total 13 1998.857143 Copy Data Answer 田 Tables 国 Keypad Keyboard Shortcuts O Yes O No
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What statistical mothod allows for a samultancous test of difforoncos botwoen many moans (such as pictured below)? South West East North HHE Select one O a Chi-squared ObA Test of Two Proportions OcA Test of Two Means Od Simple Regression O e ANOVA - Analysis of Variance Clear my choice hp B0
Chicken diet and weight: Compare the effects of six types of feed: casein, horsebean, linseed, meat meal, soybean, and sunflower. The ANOVA output below can be used to test for differences between the mean weights of chicks on different diets. df Sum Sq Mean Sq F value Pr(>F) feed 5 231129.16 46225.83 15.36 0.0000 residuals 65 195556.02 3008.55 If we conducted a hypothesis test to determine if these data provide convincing evidence that the mean weight of chicks varies across some (or all) groups we would find a difference between mean weight of chicks between at least two of the diets using an overall αα = 0.05. Mean SD n casein 323.58 64.43 12 horsebean 160.2 38.63 10 linseed 218.75 52.24 12 meatmeal 276.91 64.9 11 soybean 246.43 54.13 14 sunflower 328.92 48.84 12 Now use the summary above to test that casein and horsebean have a different effect on mean weights of chicks.Find the alpha level to use for this pairwise comparison to four…
Chicken diet and weight: Compare the effects of six types of feed: casein, horsebean, linseed, meat meal, soybean, and sunflower. The ANOVA output below can be used to test for differences between the mean weights of chicks on different diets. df Sum Sq Mean Sq F value Pr(>F) feed 5 231129.16 46225.83 15.36 0.0000 residuals 65 195556.02 3008.55 If we conducted a hypothesis test to determine if these data provide convincing evidence that the mean weight of chicks varies across some (or all) groups we would find a significant difference between average weight of chicks between at least two of the diets using an overall a = 0.05. Mean SD n casein 323.58 64.43 12 horsebean 160.2 linseed 218.75 38.63 10 52.24 12 meatmeal 276.91 64.9 11 soybean 246.43 54.13 14 sunflower 328.92 48.84 12 Now use the summary above to test that meatmeal and sunflower are significantly different. Fcdf = (Round to three decimal places.) The test statistic for this pairwise comparison is: t = (Round to three…
rse ations Suppose a study was done to determine whether the average amount of sleep that students get the night before an exam is less than 6 hours. An SRS of 100 students from a university was taken, and a mean of 5.5 hours was computed from the sample. The figure below provides the results of the analysis. Normal calculator Density 04 0.3 02 0.1 0 -3 -2 Mean: 0 Std. Dev. 1 Prob(X<= -2.5 )=0.0062096654 Snapshot Close Compute What is your conclusion based on the results of this study? (Assume a significance level of 0.05.) O On average, students typically get less than 6 hours of sleep the night before an exam. O On average, students typically get 6 hours of sleep the night before an exam. O On average, students typically get more than 6 hours of sleep the night before an exam. O On average, students typically get 5.5 hours of sleep the night before an exam.
Wk 5 Exercises [due Day 5] i Refer to the ANOVA table for this regression. Source d.f. 20 45 SS MS Regression Residual 1,192,019 1,602,669 59,601 35,615 Total 2,794,688 65 (a) State the degrees of freedom for the F test for overall significance. The degrees of freedom for regression are 20 and for error 45 (b) Use Appendix F to look up the critical value of Ffor a = .05. (Round your answer to 2 de es 05 (c-1) Calculate the Fstatistic. (Round your answer to 4 decimal places.) F statistic
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