The number of students in a school chorus has increased since the school first opened 6 years ago.The linear regression equation describing the change is y = 14x + 17, where a represents theyear and y represents the number of students.a. Complete the table to determine the residuals for the numberr of students. Then create a residualgraph with the X's on the x axis and residuals on the y-axis.PredictedNumber ofResidualValueYearNumber ofStudentsStudents2226405978483Residual Plot6-432-2 -1-1916escDIIF4FSF7FB@%232$123.4.78.QWERTYtabSDFGcaps lockZCVNshiftBA Clear All Draw: •b) Is the regression equation a good fit for the data?O yes, the plot has a patternO yes, the plot has no patternO no the plot has a patternO no, the plot has no patternQuestion Help: M Message instructorSubmit QuestionescDIIF3F4F7FB@%23$136.78.QWtabYASFGcaps lockshift* 00つ

Let y=a+bx be the regression line. a is the intercept and b is the slope. y is the dependent…

The number of students in a schoot chorus has increased since the school first opened The linear regression equation describing the change is y = 14x + 17, where z repre: year and y represents the number of students. a. Complete the table to determine the residuals for the number of students. Then crea graph with the x'S on the x axis and residuals on the y-axis. Predicted Number of Year Residual Value Number of Students Students 22 26 40

The number of students in a schoot chorus has increased since the school first opened The linear regression equation describing the change is y = 14x + 17, where z repre: year and y represents the number of students. a. Complete the table to determine the residuals for the number of students. Then crea graph with the x'S on the x axis and residuals on the y-axis. Predicted Number of Year Residual Value Number of Students Students 22 26 40

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 correlation for the data is r=1 and a=0.05 should regression analysis be done Find the equation of the regression line y = a+bx A= B= Find y when x=40
Use the Regression tool on the accompanying wedding data, using the wedding cost as the dependent variable and attendance as the independent variable. Complete parts a through c. Click the icon to view the wedding data. X a. What is the regression model? Wedding Cost = +(xAttendance (Round to three decimal places as needed.) Wedding Attendance and Cost Wedding Cost 62700 Attendance 300 54000 350 48000 150 40000 200 36000 250 32000 150 31000 250 29500 300 27000 250 27000 200 26000 150 25000 200 23000 200 22000 200 22000 200 21000 200 20000 100 19000 150 19000 200 18000 150 17000 100 16000 100 13000 150 8000 50 5000 50 Wedding Cost Attendance
The table shows the average weekly wages (in dollars) for state government employees and federal government employees for 8 years. The equation of the regression line is y = 1.405x – 12.307. Complete parts (a) and (b) below. Average Weekly Wages (state), x Average Weekly Wages (federal), y 751 760 791 817 835 881 924 951 1002 1047 1115 1149 1195 1250 1269 1300 (a) Find the coefficient of determination and interpret the result. 12 =O
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 63 inches. Is the result close to the actual weight of 442 pounds? Use a significance level of 0.05. Chest size (inches) 58 50 65 59 59 48 Weight (pounds) 414 312 499 450 456 260 Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? Critical Values of the Pearson Correlation Coefficient r y=D+x (Round to one decimal place as ne Critical Values of the Pearson Correlation Coefficient r NOTE: To test Ho: p=0 against H,: p+0, reject Ho if the absolute value of r is greater than the critical value in the table. a = 0.05 a = 0.01 4 0.950 0.990 0.878 0.811 0.754 5 0.959 6 0.917 7 0.875 8 0.707 0.834 0.666 0.798 10 0.632 0.765 11 0.602 0.735 12 0.576 0.708 13 0.553 0.684 14 0.532 0.661 15 0.514 0.641 16 0.497 0.623 17 0.482…
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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 data show the bug chirps per minute at different temperatures. Find the regression equation, letting the first variable be the independent (x) variable. Find the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute. Use a significance level of 0.05. What is wrong with this predicted value? Chirps in 1 min 760 1119 1125 850 965 785 D Temperature (°F) 70.5 90.8 90.8 74.7 77.1 69.9 What is the regression equation? (Round the x-coefficient to four decimal places as needed. Round the constant to two decimal places as needed.)
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 57 inches. Is the result close to the actual weight of 476 pounds? Use a significance level of 0.05. 44 Chest size (inches) Weight (pounds) 58 48 51 58 60 425 266 347 453 282 408 Click the icon to view the critical values of the Pearson correlation coefficient r. ..... What is the regression equation? y=+x (Round to one decimal place as needed.) Activate Windows View an example Get more help- Help me solve this O Type here to search hp delete insert prt sc f12 f1o fg 1 f7 f6 f5 f3 米 IOI f1 esc hom backspace 6. L. 4 U E R tab F G J. A caps lock pause 00 9, %24 3. %23
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 63 inches. Is the result close to the actual weight of 522 pounds? Use a significance level of 0.05. Chest size (inches) 58 50 65 59 59 48 D 414 312 499 450 456 260 Weight (pounds) Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? y=+x (Round to one decimal place as needed.) What is the best predicted weight of a bear with a chest size of 63 inches? The best predicted weight for a bear with a chest size of 63 inches is pounds. (Round to one decimal place as needed.) Is the result close to the actual weight of 522 pounds? O A. This result is not very close to the actual weight of the bear. O B. This result is exactly the same as the actual weight of the bear. O C. This result is close to the actual weight of the…
Annual high temperatures in a certain location have been tracked for several years. Let X represent the year and Y the high temperature. Assume that temperature is independent each year. Based on the data shown below, calculate the regression line (each value to two decimal places). First the slope and then the y-intercept. Y X 3 4 5 67 8 00 a 9 y 10.14 10.85 11.86 11.17 7.58 9.79 7.5 x+
The table shows the amounts of crude oil (in thousands of barrels per day) produced by a certain country and the amounts of crude oil (in thousands of barrels per day) imported by the same country for seven years. The equation of the regression line is y =-1.364x+17,178.20. Complete parts (a) and (b) below. Produced, x Imported, y 5,744 5,554 5,439 5,188 5,136 5,067 D 9,132 9,677 10,017 10,193 10,149 10,075 5,756 9,328 (a) Find the coefficient of determination and interpret the result. (Round to three decimal places as needed.)
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