Tall Buildings The stories and heights (in feet) of a sample of 10 buildings in Pittsburgh are shown. Stories x 64 54 40 31 45 44 42 41 39 40 Height y 741 625 535 516 515 482 435 420 411 385 Send data to Excel The correlation coefficient for the data is r= 0.788 and a= 0.05. Should regression analysis be done OThe regression analysis should not be done. O The regression analysis should be done. Find the equation of the regression line. Round the coefficients to at least three decimal places. y' a+bx a =

Tall Buildings The stories and heights (in feet) of a sample of 10 buildings in Pittsburgh are shown. Stories x 64 54 40 31 45 44 42 41 39 40 Height y 741 625 535 516 515 482 435 420 411 385 Send data to Excel The correlation coefficient for the data is r= 0.788 and a= 0.05. Should regression analysis be done OThe regression analysis should not be done. O The regression analysis should be done. Find the equation of the regression line. Round the coefficients to at least three decimal places. y' a+bx a =

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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Help with: Determine the least-squares regression line. Test whether there is a linear relation between height and weight at the α=0.05 level of significance. What is the P Value Remove the values listed for Player 4 from the data table. Test whether there is a linear relation between height and weight. Do you think that Player 4 is influential? What is the P Value
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Attention: These data are different from your previous questions! Now Lynn takes a different approach. They collect another two samples - GPA from students taking a semester of in-class courses, and then the same students' GPA when they are taking a semester of online courses. The data set is below. They predict that they will find a difference between in-class GPA and online GPA for the same students. Differences Between GPA's Student In Class GPA Online GPA Amy 4.0 3.5 Brad 3.5 2.2 Caroline 3.7 2.0 Dan 3.5 3.5 Emily 3.6 3.3 Frank 3.2 3.2 George 3.3 2.1 What is the t-statistic for this t-test? (Round to 2 decimal places.)
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of six notable buildings in a city. Height, x Stories, y 758 621 518 510 492 | 483 | 51 47 46 43 39 36 Find the regression equation. y = ☐ X+ (a) x = 503 feet (c) x = 802 feet (b) x = 649 feet (d) x = 728 feet (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.)
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Post secondary education information was examined for a random selection of states. The data below show the number of community colleges in the number of universities for each particular state. Community: 12, 17, 13, 10, 8 University: 4, 6, 5, 4, 3 A. Create a scatterplot of the given data sets B. Find the correlation coefficient of the sets of data. C. Create the equation of the regression line for the data and evaluate it when X=300.
The personnel director of a large hospital is interested in determining the relationship (if any) between an employee's age and the number of sick days the employee takes per year. The director randomly selects ten employees and records their age and the number of sick days which they took in the previous year. Employee 1 2 3 4 5 6 7 8 Age 30 50 40 55 30 28 60 25 Sick Days 7 4 3 2 9 10 0 8 Copy Data The estimated regression line and the standard error are given. Sick Days = 14.310162 - 0.2369(Age 9 10 30 45 5 2 Se = 1.682207 Find the 95% confidence interval for the average number of sick days an employee will take per year, given the employee is 26. Round your answer to two decimal places.
Correlation and Regression Assignment A sample of 10 adult men gave the following data on their heights and weights. Height (inches) X 62 62 63 65 66 67 68 68 70 72 Weight (pounds) Y 120 140 130 150 142 130 135 175 149 168 Generate the scatter plot of this data and graph the regression line in your plot. Include a picture of this graph and explain your impression of how well the line fits the data. State the equation of the regression line. Find r (correlation coefficient). Interpret the value of r in the context of this problem. Find the coefficient of determination, r2. Explain what it means in the context of this problem. Provide examples of other lurking variables that may have an effect on weight besides height. Use a 1% level of significance to test the claim that ρ > 0. Show all steps of your hypothesis test. Predict the weight of a man whose height is 60 inches. (h) Find…
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 44 inches. Is the result close to the actual weight of 293 pounds? Use a significance level of 0.05. Chest size (inches) Weight (pounds) 45 221 265 50 41 52 45 335 307 45 265 Critical Values of the Pearson Correlation Coefficient r 321 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 a = 0.05 a = 0.01 0.990 NOTE: To test Ho: p=0 y=+x (Round to one decimal place as needed.) 4 against H,: p#0, reject H, jf the absolute value of r is greater than the critical value in the table. 0.950 0.878 0.959 6 0.811 0.917 0.754 0.875 8 0.707 0.834 9 0.666 0.798 10 0.632 0.765 11 0.602 0.735 12 0.576 0.708 0.684 0.661 13 0.553 14 0.532 15 0.514 0.641 0.497 16 17 18 19 0.623…
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