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3. Northem red oak (Quercus rubra) is a common tree species in many temperate deciduous forests in the US. Christian Wyatt and I measured diameter at breast height (DBH) and bark thickness of northern red oak trees in Swope Park in Missouri. We wanted to know if bark thickness is related to stem diameter. What is the null hypothesis? What is the alternative hypothesis? Answer the following questions using the output from R. Coefficients: (Intercept) DBH Estimate Std. Error t value Pr(>It|) 0.00647 ** 14.050 1.82e-12 *** 0.41727 0.02992 3.008 1.25534 0.42035 Signif. codes: O **** 0.001 **** 0.01 *** 0.05 .' 0.1 ' 1 Residual standard error: 0.9417 on 22 degrees of freedom Multiple R-squared: 0.8997, Adjusted R-squared: 0.8952 F-statistic: 197.4 on 1 and 22 DE, p-value: 1.819e-12 What is the equation for the best-fit linear relationship between stem diameter (DBH) and bark thickness? How much of the variation in bark thickness is explained by variation in stem diameter? . What conclusion can you make (i.e., accept or reject the null hypothesis)? Explain how you reached this conclusion.

3. Northem red oak (Quercus rubra) is a common tree species in many temperate deciduous forests in the US. Christian Wyatt and I measured diameter at breast height (DBH) and bark thickness of northern red oak trees in Swope Park in Missouri. We wanted to know if bark thickness is related to stem diameter. What is the null hypothesis? What is the alternative hypothesis? Answer the following questions using the output from R. Coefficients: (Intercept) DBH Estimate Std. Error t value Pr(>It|) 0.00647 ** 14.050 1.82e-12 *** 0.41727 0.02992 3.008 1.25534 0.42035 Signif. codes: O **** 0.001 **** 0.01 *** 0.05 .' 0.1 ' 1 Residual standard error: 0.9417 on 22 degrees of freedom Multiple R-squared: 0.8997, Adjusted R-squared: 0.8952 F-statistic: 197.4 on 1 and 22 DE, p-value: 1.819e-12 What is the equation for the best-fit linear relationship between stem diameter (DBH) and bark thickness? How much of the variation in bark thickness is explained by variation in stem diameter? . What conclusion can you make (i.e., accept or reject the null hypothesis)? Explain how you reached this conclusion.

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter10: Statistics
Section10.6: Summarizing Categorical Data
Problem 32PPS
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reached this conclusion. Write a sentence as you would for the results section of a paper.
Transcribed Image Text:reached this conclusion. Write a sentence as you would for the results section of a paper.
BIUA- A - 3. Northem red oak (Quercus rubra) is a common tree species in many temperate deciduous forests in the US. Christian Wyatt and I measured diameter at breast height (DBH) and bark thickness of northern red oak trees in Swope Park in Missouri. We wanted to know if bark thickness is related to stem diameter. What is the null hypothesis? What is the alternative hypothesis? Answer the following questions using the output from R. Coefficients: Estimate Std. Error t value Pr(>|t|) 0.00647 3.008 (Intercept) DBH 1.25534 0.41727 0.42035 0.02992 14.050 1.82e-12 *** o. *** 0.05 ',' 0.1 ' '1 Signif. codes: O **** 0.001 *** Residual standard error: 0.9417 on 22 degrees of freedom I Multiple R-squared: F-statistic: 197.4 on 1 and 22 DF, 0.8997, Adjusted R-squared: p-value: 1.819e-12 0.8952 What is the equation for the best-fit linear relationship between stem diameter (DBH) and bark thickness? How much of the variation in bark thickness is explained by variation in stem diameter? What conclusion can you make (i.e., accept or reject the null hypothesis)? Explain how you reached this conclusion.
Transcribed Image Text:BIUA- A - 3. Northem red oak (Quercus rubra) is a common tree species in many temperate deciduous forests in the US. Christian Wyatt and I measured diameter at breast height (DBH) and bark thickness of northern red oak trees in Swope Park in Missouri. We wanted to know if bark thickness is related to stem diameter. What is the null hypothesis? What is the alternative hypothesis? Answer the following questions using the output from R. Coefficients: Estimate Std. Error t value Pr(>|t|) 0.00647 3.008 (Intercept) DBH 1.25534 0.41727 0.42035 0.02992 14.050 1.82e-12 *** o. *** 0.05 ',' 0.1 ' '1 Signif. codes: O **** 0.001 *** Residual standard error: 0.9417 on 22 degrees of freedom I Multiple R-squared: F-statistic: 197.4 on 1 and 22 DF, 0.8997, Adjusted R-squared: p-value: 1.819e-12 0.8952 What is the equation for the best-fit linear relationship between stem diameter (DBH) and bark thickness? How much of the variation in bark thickness is explained by variation in stem diameter? What conclusion can you make (i.e., accept or reject the null hypothesis)? Explain how you reached this conclusion.
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