6. What is the conclusion if the regression coefficient of the variable diameter at breast height is tested?O A. Weight of tree is dependent on diameter at breast height.B. Weight of tree is independent with diameter at breast height.O C. Weight of tree is linearly dependent on diameter at breast height.O D. Weight of tree is not linearly dependent on diameter at breast height. For items 1 to 6: It is beneficial to be able to estimate the weight of a tree based on measurements of the treetaken before its harvest. Measurements on two variables were taken from a random sample of trees, whichwere subsequently harvested, and the actual weight (in kg) of the products were determined. The variablesmeasured 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).Suppose that the assumptions of linear regression were satisfied. A multiple linear regression model forpredicting the weight of tree using diameter at breast height, height of tree, and embryo type was fitted. Thesoftware output is summarized below. Use alpha=5%.InterceptDBHheightEstimate-1015.4420.983164.0089.183type_monocot -161.278Multiple R-squaredStd. Error141.62239.6265.48688.177Adjusted R-squared0.9703tc-7.1704.1391.674-1.829p-value0.00053830.00200.01440.16950.1414p-value (model)

6. The study is about the regression coefficient of the variable diameter at breast height is…

Answered: 6. What is the conclusion if the…

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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There is no linear relationship between two interval-ratio variables when the regression line on a scatterplot a. is parallel to the horizontal axis b. does not touch all of the scores c. is not an equal distance from all of the scores d. is bimodal
Data were obtained about women belonging to a gym. The women had an average height of 67 inches with an SD of 3 inches, and they had an average weight of 160 pounds, with an SD of 15 pounds. The correlation between height and weight was r=0.45. A scatterplot was made of the data with height on the horizontal axis and weight on the vertical axis; it was football shaped. 2. (a) Using the regression line, a woman who is 6 feet tall is predicted to weigh pounds. (b) The typical size of the errors for predictions made using the regression line is pounds. (c) What percent of all the women weigh more than 180 pounds? (d) What percent of women that are 6 feet tall weigh more than 180 pounds?
Q2) Find the regression line for the following data, then predict the value of y when x is 5: X 0 2 4 6 8 y 2 4 3 8 10
A diligent statistics student recorded the length of hisfaithful #2 pencil as he worked away on his homework.He discovered a strong linear relationship between thenumber of hours that he worked and the length of hispencil. Here is the regression analysis for these data.Dependent variable: length (cm)R2 = 92.3, R2 1adj2 = 89.5,coeff se t ratio p valueconstant 17.047 0.128 23.58 60.0001time (hr) -1.914 0.047 35.28 60.0001 a) Write the equation of the least square regressionline.b) Interpret R2 in this context.c) Interpret the equation in this context.d) This student’s girlfriend tried out his model on apencil she had used for 5 hours, and found a residualof -0.88 cm. How long was her pencil at that time?e) Should she have expected this model to describe therate for her pencils? Why or why not?
A tstatistic reported in the Excel linear regression output associated with an individual independent variable can be used to test: O a. if all slopes are O or not. O b. if the intercept is O or not. O c. ifa random slope is O or not. O d. if the slope associated with that independent variable is O or not. O e. if all coefficients are O or not.
More cholesterol Look again at Exercise 18’s regressionoutput for age and cholesterol level.a) The output reports s = 46.16. Explain what thatmeans in this context.b) What’s the value of the standard error of the slope ofthe regression line?c) Explain what that means in this context.
A realty company would like to develop a regression model to help it set weekly rentai rates for beach properties (y). The independent variables for this model are the number of bedrooms a property has (x). its age (x2), and the number of biocks away from the ocean it is (x). Use the accompanying data to complete parts a through e below. E Click the icon to view the rental property data. a) Using technology, construct a regression model using all three independent variables. -(8992 6) (295.6)x + (41.7) x2 + (-3146.3) x (Round to one decimal place as needed.) b) Test the significance of each independent variable using a= 0.05. Test the significance of x. Identify the null and alternative hypotheses. Ho: , = 0 H: B, 0 (Type integers or decimals.) Calculate the appropriate test statistic. The test statistic is 1.24 (Round to two decimal places as needed.) Determine the appropriate critical value(s) for a0.05. The critical value(s) is(are) (Round to two decimal places as needed. Use a…
The accompanying table shows the percentage of employment in STEM (science, technology, engineering, and math) occupations and mean annual wage (in thousands of dollars) for 1616 industries. The equation of the regression line is ModifyingAbove y with caret equals=1.125x+46.695. Use these data to construct a 90% prediction interval for the mean annual wage (in thousands of dollars) when the percentage of employment in STEM occupations is 12% in the industry. Interpret this interval. Construct a 90% prediction interval for the mean annual wage (in thousands of dollars) when the percentage of employment in STEM occupations is 12% in the industry. nothingless than<yless than<nothing (Round to three decimal places as needed.) Interpret the prediction interval. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to the nearest whole number as needed.) A. One can be 90% confident that the mean annual wage will…
A study was conducted to determine if a linear relationship exists between Calculus II (Y) grades and Calculus I (X). The researcher found out that the values of the slope and the y-intercept of the regression line is equal to 1.0134 and – 5.239, respectively. What is the predicted Calculus II grade when the Calculus I grade is equal to 85?
A researcher is proposing that exercise makes a person more energized as a result they require less sleep. He carries out a survey on the number of hours of exercise per week and the average hours of sleep needed per night in order to feel well rested. The results are shown on page 2 for the 8 participants. Calculate and interpret the regression line for the data. Hours of exercise/week (x) Average hours of sleep needed/night (Y) 8.6 4 8.1 5.2 9 2 8.5 3.4 7.4 8 6.8 10 9.4 1.5 7.7 6
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