A department of transportation's study on driving speed and millage for midsize automobiles resulted in the following data. Driving 30 Speed Millage | 28 a) Find the equation of regression line and interpret slope coefficient. Show all summations required for the computation of slope and y-intercept. b) Compute and interpret the sample correlation coefficient and coefficient of determination for these data. Also, find standard error of estimates and interpret. 50 40 55 30 25 60 25 50 55 25 25 23 30 32 21 35 26 25

A department of transportation's study on driving speed and millage for midsize automobiles resulted in the following data. Driving 30 Speed Millage | 28 a) Find the equation of regression line and interpret slope coefficient. Show all summations required for the computation of slope and y-intercept. b) Compute and interpret the sample correlation coefficient and coefficient of determination for these data. Also, find standard error of estimates and interpret. 50 40 55 30 25 60 25 50 55 25 25 23 30 32 21 35 26 25

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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The following table shows the starting salary and profile of a sample of 10 employees in a certain call center agency. Run a multiple regression analysis with starting salary as the dependent variable (pesos) and GPA, years of experience and civil service ratings as the independent variables. Use .05 level of significance. Copy-paste the data and run the analysis using MS Excel. starting salary GPA Years of experience Civil Service Ratings 15000 80.1 1 79.5 15000 81.2 1 78.0 15500 81.3 2 79.0 16000 82.4 3 80.0 16200 83.4 3 85.0 17500 87.9 4 89.9 18000 90.3 5 89.1 16300 84.2 3 84.1 17000 87.0 4 89.0 17900 88.1 5 89.2 What is the computed R square of the resulting multiple linear regression and its interpretation?
9. Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (Each pair of variables has a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The caloric content and the sodium content (in milligrams) for 6 beef hot dogs are shown in the table below. Calories, x Sodium, y 160 130 330 120 70 190 (a) x = 170 calories (c) x = 150 calories 180 (b) x = 80 calories 420 470 360 250 530 (d) x = 210 calories Find the regression equation. x+( (Round to three decimal places as needed.) y = Choose the correct graph below. OA. О В. OC. OD. 560- 560 560 560- 200 G 0IN T> 200 200 Calories Calories Calories Calories (a) Predict the value of y for x = 170. Choose the correct answer below. O A. 411.632 O B. 543.752 O C. 455.672 O D. not meaningful (b) Predict the value of y for x = 80. Choose the correct answer below. O A. 411.632 О В. 257.492 O C.…
The following data represent the number of flash drives sold per day at a localcomputer shop and their prices.Price Units Sold34 336 432 635 530 938 240 1a. Develop the estimated regression equation that could be used to predict thequantity sold given the price. Interpret the slope.b. Did the estimated regression equation provide a good fit? Explain.c. Compute the sample correlation coefficient between the price and the number offlash drives sold. Use a= 0.01 to test the relationship between price and units sold.d. How many units can be sold per day if the price of flash drive is set to $28.
The age and prices of 11 Nissan cars given in the following data: Age (in years) 5 4 6 5 5 5 6 6 2 7 7 Price (in $100s) 85 103 70 82 89 98 66 95 169 70 48 a. Obtain the correlation coefficient between the age and price of the cars. Interpret the value of the correlation coefficient. b. Obtain a regression equation of Price (dependent variable) on Age (Independent variable). c. What will be the Price of the car after 3 years? d. Find the coefficient of determination. Determine the percent of variation that is explained by the regression equation clearly.
The systolic blood pressure of individuals is thought to be related to both age and weight. Let the systolic blood pressure, age, and weight be represented by the variables x1, x2, and x3, respectively. Suppose that Minitab was used to generate the following descriptive statistics, correlations, and regression analysis for a random sample of 15 individuals. Descriptive Statistics Variable N Mean Median TrMean StDev SE Mean x1 15 157.63 157.73 157.63 3.456 0.892335 x2 15 62.26 62.76 62.26 1.356 0.350118 x3 15 167.50 166.50 167.50 4.055 1.046996 Variable Minimum Maximum Q1 Q3 x1 123 179 139.036 166.522 x2 42 87 47.988 77.501 x3 121 237 143.387 222.976 Correlations (Pearson) x1 x2 x2 0.863 x3 0.828 0.641 Regression Analysis The regression equation is x1 = 0.858 + 0.812x2 + 0.528x3 Predictor Coef StDev T P Constant 0.858 0.723 1.19 0.129 x2 0.812 0.759 1.07 0.153 x3 0.528 0.464 1.14 0.139 S = 0.132 R-sq = 96.1 % R-sq(adj) =…
Consider the following data,Study Hours (Y): 2, 4 ,6 ,8 ,10 ,13, 7Sleeping Hours (X): 10, 9, 8, 7,6 ,7, 5 i) Calculate and analyze the fitted regression line between the number of study hours and the number of sleeping hours of different intakes of CSE students.ii) Find the coefficient of determination and interpret your data.iii) Predict study hour when he/she sleeps 11 hours.
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