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For items 1 to 6: It is beneficial to be able to estimate the weight of a tree based on measurem taken before its harvest. Measurements on two variables were taken from a random sample of were subsequently harvested, and the actual weight (in kg) of the products were determined. measured are trunk diameter at breast height or DBH (measured about 4 feet from ground lev height of tree (in feet), and embryo type (monocot or dicot). linear relationship between weight and dian 3. Based on the R output below, there is a height among trees. Pearson's product-moment correlation data: weight and DBH t = 13.011, df = 6, p-value = 1.27e-05 alternative hypothesis: true correlation is not equal to 0 95 percent confidence interval: 0.9042967 0.9969877 sample estimates: cor 0.9827369 O A. very weak direct O B. very weak inverse O C. very strong direct D. very strong inverse

For items 1 to 6: It is beneficial to be able to estimate the weight of a tree based on measurem taken before its harvest. Measurements on two variables were taken from a random sample of were subsequently harvested, and the actual weight (in kg) of the products were determined. measured are trunk diameter at breast height or DBH (measured about 4 feet from ground lev height of tree (in feet), and embryo type (monocot or dicot). linear relationship between weight and dian 3. Based on the R output below, there is a height among trees. Pearson's product-moment correlation data: weight and DBH t = 13.011, df = 6, p-value = 1.27e-05 alternative hypothesis: true correlation is not equal to 0 95 percent confidence interval: 0.9042967 0.9969877 sample estimates: cor 0.9827369 O A. very weak direct O B. very weak inverse O C. very strong direct D. very strong inverse

MATLAB: An Introduction with Applications
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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For items 1 to 6: It is beneficial to be able to estimate the weight of a tree based on measurements of the tree taken before its harvest. Measurements on two variables were taken from a random sample of trees, which were subsequently harvested, and the actual weight (in kg) of the products were determined. The variables measured are trunk diameter at breast height or DBH (measured about 4 feet from ground level; in inches), height of tree (in feet), and embryo type (monocot or dicot). linear relationship between weight and diameter at breast 3. Based on the R output below, there is a height among trees. Pearson's product-moment correlation data: weight and DBH t = 13.011, df = 6, p-value = 1.27e-05 alternative hypothesis: true correlation is not equal to 0 95 percent confidence interval: 0.9042967 0.9969877 sample estimates: 0.9827369 cor O A. very weak direct O B. very weak inverse O C. very strong direct O D. very strong inverse
Transcribed Image Text:For items 1 to 6: It is beneficial to be able to estimate the weight of a tree based on measurements of the tree taken before its harvest. Measurements on two variables were taken from a random sample of trees, which were subsequently harvested, and the actual weight (in kg) of the products were determined. The variables measured are trunk diameter at breast height or DBH (measured about 4 feet from ground level; in inches), height of tree (in feet), and embryo type (monocot or dicot). linear relationship between weight and diameter at breast 3. Based on the R output below, there is a height among trees. Pearson's product-moment correlation data: weight and DBH t = 13.011, df = 6, p-value = 1.27e-05 alternative hypothesis: true correlation is not equal to 0 95 percent confidence interval: 0.9042967 0.9969877 sample estimates: 0.9827369 cor O A. very weak direct O B. very weak inverse O C. very strong direct O D. very strong inverse
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