The regression results obtained for the models:Model A: BalanceModel B: Balance ==Model C: Balance =VariableInterceptare summarized in the following table.TimePrimeTimex Prime60 +61Prime + ε60 +61 Time + 62 Prime + 63 Time × Prime + ɛ60 +61 Prime + 6₂Time x Prime + ε,Model A88,020 (t = 77.89)N/A-18,000 (t -11.26)N/A=1,532,480,000Model B90,269 (t = 24.35)-148 (t H -0.64)-28,493 (t -5.36)662 (t 2.03)=0.72540.7198F•1,369,126,091Model C88,020 (tN/A-26,244 (t = -6.66)514 (t = 2.27)0.75470.738881.19)SSER²Adjusted R²Note: The values of relevant test statistics are shown in parentheses beside the estimated coefficients.Using Model B, which of the following is the alternative hypothesis for testing the significance of Time?1,381,128, 2990.75260.7421

The objective of the question is to identify the alternative hypothesis for testing the significance…

Answered: The regression results obtained for the…

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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Give the equation of the regression line: -913.2969+0.4808years(y) a) Plug an actual x value into the equation and discuss the difference between the real y and the predicted yb) Discuss the domain of your datac) Include the scatterplot with line of best fit
A hydrologist is interested in studying the influence of rainfall on runoff in a drainage basin. Rainfall and runoff are measured during 20 rainfall events. Model the relationship. What are the variables and the type of measurement for these variables? slope (numerical) and itercept (numerical) dependent variable (nominal) and independent vatiable (nominal) Rainfall (total mm) and Runoff (liters/36 hours) geographic location (lat/long), area of watershed (hectares), and substrate type (rock/soil/vegitation) rainfall (numerical) and runoff (numerical)
The regression equation to predict the total world gross ticket sales from the opening weekend ticket sales is: WorldGross^=9.23+6.87⋅OpeningWeekend Interpret the y-intercept of the regression line in context.
Develop a scatterplot and explore the correlation between customer age and net sales by each type of customer (regular/promotion). Use the horizontal axis for the customer age to graph. Find the linear regression line that models the data by each type of customer. Round the rate of changes (slopes) to two decimal places and interpret them in terms of the relation between the change in age and the change in net sales. What can you conclude? Hint: Rate of Change = Vertical Change / Horizontal Change = Change in y / Change in x
Assuming equal effort (# of nets in the water has not changed and the fishing season dates have stayed the same) identify trends in the squid population you see in the data. Based on your textbook reading this week, speculate what processes or dynamics could produce the population trends seen in your data.
A researcher is studying the intensity of hurricanes that entered the Gulf of Mexico between 1975-2015 and the average water temperature of the Gulf of Mexico at the hurricane's peak strength. What is the independent and dependent variable in this study?
Write the linear model to test the hypothesis that there is no treatment effect. Clearly describe each term in the model, and the range of the subscripts. Write the null hypothesis that you are testing. Call: lm(formula = score ~ list, data = hearing) Residuals: Min 1Q Median 3Q Max -14.7500 -5.5833 -0.2083 6.3333 16.4167 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 32.750 1.612 20.315 < 2e-16 *** listList2 -3.083 2.280 -1.352 0.17955 listList3 -7.500 2.280 -3.290 0.00142 ** listList4 -7.167 2.280 -3.144 0.00225 ** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 7.898 on 92 degrees of freedom Multiple R-squared: 0.1382, Adjusted R-squared: 0.1101 F-statistic: 4.919 on 3 and 92 DF, p-value: 0.00325
An economist at Nedbank ran a study of the relationship between FTSE/JSE All Shares index return (JALSH) and consumer price index (CPI) from 2006 to 2017, the data collected is shown in the Table 1 below. FTSE/JSE All Shares index return (JALSH) and consumer price index (CPI) from 2006 to 2017. Year JALSH (Y) CPI (X) 2006 0.41 4.7 2007 0.19 7.1 2008 -0.23 11.5 2009 0.32 7.1 2010 0.19 4.3 2011 0.03 5.0 2012 0.27 5.6 2013 0.21 5.7 2014 0.11 6.1 2015 0.05 4.6 2016 0.00 6.4 2017 0.21 5.3 The estimated regression…

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