3. Given the following regression:Wage = 10 + 1.2 x male + 2 x educ + 0.15 x (male x educ) + uThe dependent variable is hourly wage. There are three independent variables: a binary variableindicating male, years of education, and an interaction between male and educ.(a) Plot the relationship between wage and education for males and females separately. Put wage on thevertical axis and education on the horizontal axis. (hint: see Panel (b) of Figure 8.8 in the textbook; Youmay draw the graph on software or on a piece of paper and paste the snapshot below.)(b) According to the regression function above, (1) which gender has a higher base wage (for people withno education)? (2) which gender has higher return to education? (3) what's effect of an additional year ofeducation on wage for females? (4) what's the effect of an additional year of education on wage for males?On* Accessibility: Investigate

a ) Please note that the relationship netween wage and education of male and female can be plotted…

Answered: 3. Given the following regression: Wage…

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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Suppose that you are interested in the relationship between Reading and Writing scores. (c) Compute and interpret the R2 value for the relationship between Reading and Writing scores. (d) Interpret the value of the slope in the regression model predicting Reading scores from Writing scores. RDG WRTG 34 44 47 36 42 59 39 41 36 49 50 46 63 65 44 52 47 41 44 50 50 62 44 41 47 40 42 59 42 41 47 41 60 65 39 49 57 54 73 65 47 46 39 44 35 39 39 41 48 49 31 41 52 63 47 54 36 44 47 44 34 46 52 57 42 40 37 44 44 33 71 58 47 46 42 33 42 36 47 41 52 54 52 54 39 39 31 41 60 54 47 31 39 28 42 36 47 57 42 49 36 41 50 33 34 34 55 55 28 46 42 42 44 44 60 52 39 57 36 37 44 44 39 42 39 34 42 39 42 44 52 54 65 65 42 26 47 62 52 62 44 54 52 54 47 44 65 57 63 65 60 59 47 44 65 57 53 61 68 63 55 56 39 53 52 52 65 67 52 44 57 67 63…
Breakfast cereals We saw in Chapter 7 that the calorie con-tent of a breakfast cereal is linearly associated with its sugar content. Is that the whole story? Here’s the output of aregression model that regresses Calories for each serving onits Protein(g), Fat(g), Fiber(g), Carbohydrate(g), andSugars(g) content.Dependent variable is CaloriesR-squared = 84.5, R-squared (adjusted) = 83.4,s = 7.947 with 77 - 6 = 71 degrees of freedomSource Sum ofSquares dfMeanSquare F-RatioRegression 24367.5 5 4873.50 77.2Residual 4484.45 71 63.1613Variable Coefficient SE(Coeff) t-Ratio P-ValueIntercept 20.2454 5.984 3.38 0.0012Protein 5.69540 1.072 5.32 60.0001Fat 8.35958 1.033 8.09 60.0001Fiber -1.02018 0.4835 -2.11 0.0384Carbo 2.93570 0.2601 11.3 60.0001Sugars 3.31849 0.2501 13.3 60.0001Assuming that the conditions for multiple regressionare met,a) What is the regression equation?b) Do you think this model would do a reasonably goodjob at predicting calories? Explain.c) To check the conditions, what…
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
Regression establishes functional relationship between and variable. a. Cross and Managerial O b. Mutual and Managerial O C. Average and Mutual O d. Independent and dependent
I. Show complete solutions. Simple Linear Regression and Correlation: a.) Results of a study on the occurrence of sodium and chloride in surface streams in a coastal area. The following data are chloride concentration (y) in mg/liter and road-way area in the watershed (x) in %. Y 0.24 4.6 1. What is the value of the correlation coefficient? 2. What is the interpretation for this case? 3. What is the estimated chloride concentration if road way 0.3 6.4 0.45 9.8 area in the watershed is 1.30% 0.75 10.7 4. What is the equation of the prediction line? 0.57 10.6 0.75 10.9 0.4 11.7 0.8 12.5 0.6 14 0.78 14.7 0.85 15.1 0.68 18.3 0.69 19.2 1.4 23.1 1.15 27.3 1.05 27.7 1.69 32 1.62 38.4
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Are the years of education of a child dependent on the years of education of their parent? The table shows the number of years of education of parent and the number of years of education of their child. Years of Education of Parent 13 9 7 12 12 10 11 Years of Education of their Child 13 11 7 16 17 9 17 If there is a significant linear correlation between the variables, determine the regression equation. Are the years of education of a child dependent on the years of education of their parent? The table shows the number of years of education of parent and the number of years of education of their child. Years of Education of Parent 13 9 7 12 12 10 11 Years of Education of their Child 13 11 7 16 17 9 17 If there is a significant linear correlation between the variables, determine the regression equation. y’ = 1.5x - 3 There is no significant correlation between the variables,…
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