Question 15y =y32.9833.5630.3429.1225.824.9822.561021.841119.7212 19.8Based on the data shown below, calculate the regression line (each value to two decimal places)X3454016789TQuestion Help: VideoSubmit Question<>X +

Sample size : n=10xy332.98433.56530.3462912725.8824.95922.561021.841119.721219.8∑x=75∑y=3143.55The…

Answered: Question 15 Based on the data shown…

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 data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 40 inches. Is the result close to the actual weight of 352 pounds? Use a significance level of 0.05. Chest size (inches) *Weight (pounds) 44 54 328 528 41 55 39 51 418 580 296 503 Click the icon to view the critical values of the Pearson correlation coefficient r. - What is the regression equation? x (Round to one decimal place as needed.)
The following data are the monthly salaries and the grade point averages for students who obtained a bachelor's degree in mathematics. GPA: 2.6, 3.4, 3.6, 3.2, 3.5, and 2.9; Monthly Salary: 330o, 3600, 4000, 3500, 3900, and 3600. Plot the scatter diagram showing the deviations about the estimated regression line and the line y = y(bar).
It is inferred that the tip amount has a relationship with value of a dinner bill. The collected data is presented in the table. Conduct a regression analysis. X - Bill ($) 33.46 50.68 87.92 98.84 63.60 107.34 Y - Tip ($) 5.70 5.00 8.08 17.00 12.00 16.00
Find the multiple regression model of the given data: y A B с D E F 8.0 19.6 94.9 5.2 2.3 2.1 29.6 8.3 19.8 89.7 5.2 1.8 2.1 32.4 8.5 19.6 96.2 5.5 2.0 2.1 31.0 8.8 18.6 95.6 5.8 1.9 2.0 32.4 9.0 18.8 86.5 6.4 1.8 2.2 32.6 9.3 20.4 84.5 5.8 2.1 2.1 32.2 9.5 20.8 88.9 5.5 1.9 2.2 31.8 Suppose that the regressors are grouped by Group 1: A, C, and F; and Group 2: B, D, and E. Find the multiple regression model.
Consider the following data set, where y is the final grade in a math class and is the average number of hours the student spent working on math each week. hours/week X 6.5 10 11 12.5 13 14.5 15 17.5 19.5 20 Grade y 66.1 63 71.4 72.5 79.2 94.3 95 91.5 100 98 The regression equation is y = 3x + 41.3. a) Explain what the value of the slope means in this situation, where y is the final grade in a math class and is the average number of hours the student spent working on math each week. O For each additional hour per week that a student studies on average, their final grade will be about 3 points. O For each additional hour per week that a student studies on average, their final grade will be about 41.3 points higher. For each additional hour per week that a student studies on average, their final grade will be about 3 points higher. O For each additional hour per week that a student studies on average, their final grade will be about 41.3 points. b) Explain what the value of the…
consider the following points (1.3,2.4) (2.5,2.4) (3.3,2) (4.2,1.8) (5.1,1.6) find the equation of the regression line (round the values 2 decimal placed.
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Run a regression analysis on the following data set, where y is the final grade in a math class and x is the average number of hours the student spent working on math each week. hours/week Grade y 8. 72.2 8. 58.2 10 60 11 71.4 14 92.6 14 76.6 14 75.6 14 83.6 15 81 20 100 State the regression equation with constants accurate to 2 decimal places. ý = What is the predicted value for the final grade when a student spends an average of 15 hours each week on math? Round to 2 decimal places. Question Help: D Video 1 Video 2 Submit Question
Bluereef real estate agent wants to form a relationship between the prices of houses, how many bedrooms, House size in sq ft and Lot Size in sq ft. The data pertaining to 100 houses were processed using MINITAB and the following is an extract of the output obtained: The regression equation is Price = B + ¢Bedroom + yHouse Size + ALot Size Predictor Сoef SE Coef т P Constant 37718 14177 2.66 ** Bedrooms 2306 6994 0.33 0.742 House Size 74.3 52.98 0.164 Lot Size -4.36 17.02 -0.26 0.798 S= 25023 R-Sq=56.0% R-Sq(adj)=54.6% Source DF MS F P Regression 3 76501718347 25500572782 Residual Error 96 60109046053 626135896 Total 99 • Is y significantly different from -0.5? Perform the F test at the 1% level, making sure to state the null and alternative hypotheses. Give an interpretation to the term “R-sq" and comment on its value.
An automobile rental company wants to predict the yearly maintenance expense (Y) for an automobile using the number of miles driven during the year () and the age of the car (, in years) at the beginning of the year. The company has gathered the data on 10 automobiles and run a regression analysis with the results shown below:. Summary measures Multiple R 0.9689 R-Square 0.9387 Adj R-Square 0.9212 StErr of Estimate 72.218 Regression coefficients Coefficient Std Err t-value p-value Constant 33.796 48.181 0.7014 0.5057 Miles Driven 0.0549 0.0191 2.8666 0.0241 Age of car 21.467 20.573 1.0434 0.3314 Use the information above to estimate the annual maintenance expense for a 10 years old car with 60,000 miles.
Based on the data shown below, calculate the regression line. y 1 4.27 3.64 3 3.31 5.08 5.85 6. 2.42 y = [three decimal accuracy] [three decimal accuracy] 45

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Question 15 Based on the data shown below, calculate the regression line (each value to two decimal places) y = y 32.98 33.56 30.34 29.12 25.8 24.98 22.56 21.84 11 19.72 12 19.8 X 3 4 5 6 7 8 9 10 Question Help: Video Question X +