Using 1% & 5% alphas, test the overall significance of the model on excel. SUMMARYOUTPUTRegression StatisticsMultiple RR SquareAdjusted RSquareStandard Error 0.648011208ObservationsANOVARegressionResidualTotalInterceptfixed acidity;volatile aciditycitric acidresidual sugarchloridesfree sulfurdioxidetotal sulfurdioxidedensitypHsulphatesalcohol0.6004595770.3605517030.356119484df15991587159811 375.754403 34.159491160.419918526CoefficientsSS-0.182563950.01633127-1.874225160.004361333MS666.41071042.1651t StatF81.3479022P-valueStandard63.53751785 -19.6071009463.53751785Error21.96520845 21.194575 1.036359939 0.300192136 -19.607100940.024990553 0.0259485 0.963082682 0.335652752 -0.025906394 0.075887499 -0.025906394 0.075887499-1.08359026 0.12110128 -8.947801896 9.87236E-19 -1.321125565 -0.846054953 -1.321125565 -0.846054953Significance F1.7914E-1450.41928321 -4.470069717 8.37395E-060.00217129 2.008635263 0.044744951Lower 95%Upper 95%Lower 95.0%Upper 95.0%0.14717619 -1.240444878 0.214994246 -0.471244142 0.106116245 -0.471244142 0.1061162450.0150021 1.088599183 0.276495961 -0.013094741 0.04575728 -0.013094741 0.04575728-17.8811638 21.6330999 -0.826565029 0.408607897 -60.31362221-0.41365314 0.19159736 -2.158970991 0.031001886 -0.7894636880.916334413 0.11433747 8.014297061 2.12723E-15 0.6920660570.276197699 0.02648359 10.42901431 1.12303E-24 0.224251206-2.69663236 -1.051817956 -2.69663236 -1.0518179560.000102431 0.008620235 0.000102431 0.008620235-0.00326458 0.00072873 -4.47982984 8.00461E-06 -0.004693951 -0.001835208 -0.004693951 -0.00183520824.55129454 -60.31362221 24.55129454-0.0378426 -0.789463688 -0.03784261.140602768 0.692066057 1.1406027680.328144192 0.224251206 0.328144192

Introduction: The overall significance of the model must be tested at the 1% and 5% significance…

Answered: Using 1% & 5% alphas, test the overall…

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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State the empirical rule for variables.
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The EPA records data on the fuel economy of many different makes of cars. They are interested in determining if one could predict the mileage of the car (in miles per gallon) from the weight of the car (in pounds). What is the response variable to this study?
They then decided to determine whether the effect of the phone depended on how dependent people were on their phones. They had participants complete a scale to measure phone dependence (e.g., I would have trouble getting through a normal day without my phone) and classified them as high or low in dependence. They then analysed working memory task performance in a 2 (location: outside, desk) x 2(dependence: high, low) ANOVA. In this design, "dependence" is a(n) O a. Independent variable O b. Extraneous variable O c. Dependent variable O d. Subject variable
please please answer fast please please answer super super fast
Provide an example of a regression that arguably would have a high value of R² but would produce biased and inconsistent estimators of a causal effect. Explain why the R² is likely to be high. Explain why the OLS estimators would be biased and inconsistent.
Explain and provide examples of how one would use Hypothesis test, regression analysis, and ANOVA.
In order to explain the U.S. defense budget, the following variables are considered. Data from 1962-1981 is collected. Variable Definition Y Defense budget-outlay for year t, $ billions X2 GNP for year t, $ billions X3 U.S. military sales/assistance in year t, $ billions X4 Aerospace industry sales, $ billions Dependent Variable: Y Method: Least Squares Date: 11/22/21 Time: 11:20 Sample: 1962 1981 Included observations: 20 Variable Coefficient Std. Error t-Statistic Prob. X2 0.016703 0.007017 2.380261 0.0301 X3 -0.696174 0.453978 -1.533497 0.1447 X4 1.467729 0.277608 5.287047 0.0001 22.77514 3.311695 6.877186 0.0000 R-squared 0.971088 Mean dependent var 83.86000 Adjusted R-squared 0.965667 S.D. dependent var 28.97771 S.E. of regression Sum squared resid 5.369339 Akaike info criterion 6.376143 461.2769 Schwarz criterion 6.575290 Log likelihood -59.76143 Hannan-Quinn criter. 6.415019 F-statistic 179.1337 Durbin-Watson stat 0.676777 Prob(F-statistic) 0.000000
You are conducting a study to see if the proportion of voters who prefer Candidate A is significantly different from 0.74. Your sample data produce the test statistic z=2.133. Find the p-value accurate to 4 decimal places.
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