4. Suppose you obtain the following estimated regression model:Y₁ = 50.5 +2.05X₁ +5.25 X2 + 4.02 X3 + 0.35IncomeY; represents seasonal gas sales in Los Angeles County (in millions of dollars).© All Rights ReservedX₁ = a dummy variable that is 1 if the season is spring and 0 otherwiseX₂ = a dummy variable that is 1 if the season is summer and 0 otherwiseX3 = a dummy variable that is 1 if the season is fall and 0 otherwiseIncome = the median family income (in 1,000 of dollars) in Los Angeles County.a) Verbally interpret the coefficient of X2.b) Which season is the base case?c) Numerically, in dollars, what will be the difference in sales between spring and fall?

Given information: The regression equation is, Yi=50.5+2.05X1+5.25X2+4.02X3+0.35Income

Answered: 4. Suppose you obtain the following…

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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z score z score for each for each value of value of Zzły х х -0.278 0.536 -0.149 -0.089 0.696 -0.062 -1.253 -1 -1.652 2.070 -0.714 -0.928 0.663 2.461 1.473 1.671 0.536 0.371 0.199 -0.089 4 -0.278 0.025 Σ: ỹ = 3.857 S, = 3.078 = 5.207 T= 4.286 s, = 3.200
If the R-squared for a regression model relating the outcome y to an explanatory variable x is 0.9. This implies that there is a positive linear relationship between y and x. True or false?
The number of initial public offerings of stock issued in a 10-year period and the total proceeds of these offerings (in millions) are shown in the table. The equation of the regression line is y = 48.314x+18,056.64. Complete parts a and b. 67 197 152 Issues, x 415 458 681 481 483 377 66 Proceeds, 19,061 29,468 43,357 30,436 65,907 65,385 20,287 10,145 31,744 27,934 ly (a) Find the coefficient of determination and interpret the result. 0.284 (Round to three decimal places as needed.) How can the coefficient of determination be interpreted? The coefficient of determination is the fraction of the variation in proceeds that is unexplained and is due to other factors or sampling error. The remaining fraction of the variation is explained by the variation in issues. The coefficient of determination is the fraction of the variation in proceeds that can be explained by the variation in issues. The remaining fraction of the variation is unexplained and is due to other factors or to sampling…
4. Our R² implies that lots of stuff, other than health, also affects doctor visits. One such thing is a person's insurance status. The data file includes a third variable that records whether the person had health insurance during 2019. Estimation a regression of the form y = Bo + B₁x1 + B₂x₂ where x₁ is the health status variable from above, but now x₂ records whether the person had insurance. a) Interpret the estimate of B₁ in words. b) Interpret the estimate of B₂ in words. c) Forecast a person's number of doctor visits in 2019 if he/she was in excellent health, but did not have insurance. d) Forecast a person's number of doctor visits in 2019 if he/she was in poor health, and did have insurance. e) The R² for this regression is
You may need to use the appropriate technology to answer this question. A regression analysis involving 45 observations relating a dependent variable and two independent variables resulted in the following information. ý = 0.406 + 1.3385X, + 2X2 The SSE for the above model is 43. When two other independent variables were added to the model, the following information was provided. ý = 1.9 – 3X + 12X2 + 4Xg + 8x, This model's SSE is 36. At a 0.05 level of significance, test to determine if the two added independent variables contribute significantly to the model. State the relevant null and alternative hypotheses. O Ho: One or more of the parameters is not equal to zero. H₂: B₁ = B₂= B3 =B4 = 0 O Ho: One or more of the parameters is not equal to zero. H₂: B3 =B4 = 0 O Ho: B3 = P4 = 0 H₂: None of the parameters are equal to zero. ⒸH₁: B3 =B₁ = 0 H: One or more of the parameters is not equal to zero. O Ho: B₁ = P₂ = B3 =B4 = 0 H: One or more of the parameters is not equal to zero. ✔ Find…
Which of the following is true of a linear regression line? a. Located as close as possible to all the points of a scatter chart. B. Is defined by an equation having 2 parameters: the slope and the intercept c. Provides an approximate relationship between the values of two parameters d. All of the above
You decide to add a second independent variable to your regression. Male is a dummy variable that equals 1 if the individual is male and 0 otherwise. Your regression results are now: wage = 3.071 + 0.289 × Years of Schooling + 1.28 × Male (0.143) (0.0168) (0.624) Interpret the coefficients from this regression. Make sure to clearly indicate what is changing and what is constant in each interpretation. Determine whether each coefficient is statistically significant at each of the conventional significance levels. The R2 for this regression is 0.316. Interpret the meaning of this value.
If the equation of the regression line that relates income in dollars of student’s parents, xx, with cost in dollars of tuition,yy, is y=8500+0.018xy=8500+0.018x. a. What is the best prediction for the tuition of students whose parents earn no income? b. What is the best prediction for the tuition of students whose parents earn $45000? c. What is the best prediction for the tuition of students whose parents earn $80000?
A linear regression analysis reveals a strong, negative linear relationship between x and y. Which of the following could possibly be the results from this analysis? (A) ŷ 13.1 27.4x, r = 0.85 (B) == 27.4+ 13.1x, r = -0.95 (D) == (C) ŷ 13.1+ 27.4x, r = 0.95 542 385x, r = -0.15 (E) 0.85 0.25x, r = -0.85

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