2. The authors of the paper "Age, Spacing and Growth Rate of Tamarix as an Indication ofLake Boundary Fluctuations at Sebkhet Kelbia, Tunisia" (J. of Arid Environ. (1982):43-51) used a simple linear regression model to describe the relationship between y = vigor(average width in centimeters of the last two annual rings) and x(stems/m?). Data on which the estimated model was based is as follows.4= stem density69141515192122y.751.20.55.60.65.55.35.45.40Construct a scatter plot for the data.a)b) Find the estimated regression line and draw it on your scatter plot.Determine and interpret the coefficient of determination.c)d) What is your estimate of the average change in vigor associated with a 1-unit increase instem density?What would you predict vigor to be for a plant whose density was 17 stems/m2?e)

a/b). Given, the data on vigor and stem density. The excel step to obtain the scatter plot for the…

2. The authors of the paper "Age, Spacing and Growth Rate of Tamarix as an Indication of Lake Boundary Fluctuations at Şebkhet Kelbia. Tunisia" (J. of Arid Environ. (1982):43- 51) used a simple linear regression model to describe the relationship between y = vigor (average width in centimeters of the last two annual rings) and x = stem density (stems/m?). Data on which the estimated model was based is as follows. 4 5 9 14 15 15 19 21 22 y .75 1.20 .55 .60 .65 .55 .35 .45 .40

2. The authors of the paper "Age, Spacing and Growth Rate of Tamarix as an Indication of Lake Boundary Fluctuations at Şebkhet Kelbia. Tunisia" (J. of Arid Environ. (1982):43- 51) used a simple linear regression model to describe the relationship between y = vigor (average width in centimeters of the last two annual rings) and x = stem density (stems/m?). Data on which the estimated model was based is as follows. 4 5 9 14 15 15 19 21 22 y .75 1.20 .55 .60 .65 .55 .35 .45 .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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An oil exploration company wants to develop a statistical model to predict the cost of drilling a new well. One of the many variables thought to be an important predictor of the cost is the number of feet in depth that the must be drilled to create the well. Consequently, the company decided to fit the simple linear regression model, where y = cost of drilling the new well (in $thousands) and x = number of feet drilled to create the well. Using data collected for a sample of n=83 wells, the following results were obtained: = 10.5 + 16.20x Give a practical interpretation of the estimate of the slope of the least squares line. An oil exploration company wants to develop a statistical model to predict the cost of drilling a new well. One of the many variables thought to be an important predictor of the cost is the number of feet in depth that the must be drilled to create the well. Consequently, the company decided to fit the simple linear regression model, where y =…
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B b. What does the scatter diagram developed in part (a) indicate about the relationship between the two variables? The scatter diagram indicates a positive linear relationship between a = average number of passing yar and y = the percentage of games won by the team. c. Develop the estimated regression equation that could be used to predict the percentage of games won given the avera passing yards per attempt. Enter negative value as negative number. WinPct =| |)(Yds/Att) (to 4 decimals) d. Provide an interpretation for the slope of the estimated regression equation (to 1 decimal). The slope of the estimated regression line is approximately So, for every increase : of one yar number of passes per attempt, the percentage of games won by the team increases by %. e. For the 2011 season, the average number of passing yards per attempt for the Kansas City Chiefs was was 5.5. Use th regression equation developed in part (c) to predict the percentage of games won by the Kansas City Chiefs.…
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