Measuring the height of a tree is usually more difficult than measuring the diameter of the tree. Therefore,many researchers use regression models to predict the height of a tree from its diameter measured at 4feet 6 inches from the ground. The following computer output shows the results of a linear regressionbased on the heights, in feet, and the diameters, in inches, recorded from 31 felled trees. Which of thefollowing statements are true about this regression model? (There is more than one statement that is true.A correct answer includes selecting ALL of the true statements.)InterceptDiameterEstimate62.0311.054Std Error4.3830.322t value14.153.27Pr(> |t)0.00000.0028The degrees of freedom is n - 1 = 30.The standard error of the height is 0.322.The degrees of freedom is n - 2 = 29.The slope of the regression line is 62.031.The slope of the regression line is 1.054.A 90 percent confidence interval for the slope of the population regression line is (0.396, 1.712).A 95 percent confidence interval for the slope of the population regression line is (0.396, 1.712).The standard error of the diameter is 0.322.

n = 31Degrees of freedom = n - 2 = 31 - 2 = 29Assume Confidence interval = 0.95Significance level…

Answered: Measuring the height of a tree is…

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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A park has kept the number of visitors since its opening in January. For the first six months of the year, the following numbers were recorded: Month Number of visitors Month Number of visitors January 133 April 640 February 183 May 1,879 March 285 June 2,550 Estimate the intercept and slope of the linear regression equation for forecasting the numbers of visitors. What are the forecasts for July through December of the year using the regression equation? The numbers of visitors to the park were 2,150 in July, and 2,660. Use Holt’s method with α=0.15 and β= 0.10 to find the one-step-ahead and two-step-ahead forecasts for September and October, respectively.
Please answer parts d, e and f.
The applet displays a scatterplot with the following points: (7,10),(27,35),(24,25),(8,12),(10,19),(15,22). Identify the slope of the regression line, intercept of the regression line, and correlation coefficient. Report your answers accurate to within two decimal places.
Researchers are interested in predicting the height of a child based on the heights of their mother and father. Data were collected, which included height of the child ( height), height of the mother ( mothersheight ), and height of the father (fathersheight ). The initial analysis used the heights of the parents to predict the height of the child (all units are inches). The results of the analysis, a multiple regression, are presented below. . regress height mothersheight fathersheight Source Model Residual Total height mothersheight fathersheight _cons SS 208.008457 314.295372 522.303829 df 2 104.004228 8.49446952 37 MS 39 13.3924059 Coef. Std. Err. .6579529 .1474763 .2003584 .1382237 9.804327 12.39987 t P>|t| 4.46 0.000 C 0.156 0.79 0.434 Number of obs = F( 2, 37) = Prob > F R-squared Adj R-squared = Root MSE = = .3591375 -.0797093 -15.32021 = 40 12.24 0.0001 0.3983 0.3657 2.9145 [95% Conf. Interval] .9567683 .4804261 34.92886 What are the null and alternative hypotheses…
This question has do with linear regression.If I consider attendance in a class versus final grade in the class can you explain where there is a positive and when there is a negative relationship between them.
The value of a sports franchise is directly related to the amount of revenue that a franchise can generate. Below is the data that represents the value (in $millions) and the annual revenue (in $millions) for 30 Major League Baseball franchises. Suppose you want to develop a simple linear regression model to predict franchise value based on annual revenue generated. Team Revenue Value Baltimore 179 460 Boston 310 1000 Chicago White Sox 214 600 Cleveland 178 410 Detroit 217 478 Kansas City 161 354 Los Angeles Angels 226 656 Minnesota 213 510 New York Yankees 439 1850 Oakland 160 321 Seattle 210 585 Tampa Bay 161 323 Texas 233 674 Toronto 188 413 Arizona 186 447 Atlanta 203 508 Chicago Cubs 266 879 Cincinnati 185 424 Colorado 193 464 Houston 196 549 Los Angeles 230 1400 Miami 148 450 Milwaukee 195…
The datasetBody.xlsgives the percent of weight made up of body fat for 100 men as well as other variables such as Age, Weight (lb), Height (in), and circumference (cm) measurements for the Neck, Chest, Abdomen, Ankle, Biceps, and Wrist. We are interested in predicting body fat based on abdomen circumference. Find the equation of the regression line relating to body fat and abdomen circumference. Make a scatter-plot with a regression line. What body fat percent does the line predict for a person with an abdomen circumference of 110 cm? One of the men in the study had an abdomen circumference of 92.4 cm and a body fat of 22.5 percent. Find the residual that corresponds to this observation. Bodyfat Abdomen 32.3 115.6 22.5 92.4 22 86 12.3 85.2 20.5 95.6 22.6 100 28.7 103.1 21.3 89.6 29.9 110.3 21.3 100.5 29.9 100.5 20.4 98.9 16.9 90.3 14.7 83.3 10.8 73.7 26.7 94.9 11.3 86.7 18.1 87.5 8.8 82.8 11.8 83.3 11 83.6 14.9 87 31.9 108.5 17.3…
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Show step by step on EXCEL. I am having a hard time on this.
A sports-equipment researcher was interested in the relationship between the speed of a golf club (in feet per second) and the distance a golf ball travels (in yards). Information was collected on several golfers and was used to obtain the regression equation ŷ = 2x - 106, where x represents the club speed and ŷ is the predicted distance. Which statement best describes the meaning of the slope of the regression line? For each increase in distance by 1 yard, the predicted club speed increases by 2 ft/sec. For each increase in distance by 1 yard, the predicted club speed decreases by 106 ft/sec. For each increase in club speed by 1 ft/sec, the predicted distance increases by 2 yards. For each increase in club speed by 1 ft/sec, the predicted distance decreases by 106 yards.
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