A simple regression analysis is performed to relate maintenance expense (Y, dollars per month) to usage (X, hours per week). A random sample of 82observations showed an F-statistic of 10 in the ANOVA table, and the scatter plot suggested that maitenance expense increases as usage increases. Thesample variance of Y is 100.Question 17. The sample correlation coefficient between X and Y is closest toO 1/4O 1/9O 1/5O 1/2O 1/3o ooo o

Answered: Image /qna-images/answer/b805f2e9-da36-4c0d-8ac6-c62bf9d3e19f.jpg

Answered: A simple regression analysis 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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Suppose the correlation coefficient r=0.16 Find:a. The coefficient of determination r2= (round to 3 decimal places)b. The percentage of explained variation = % (round to 1 decimal place)c. The percentage of unexplained variation = % (round to 1 decimal place)
A researcher at a large company has collected data on the beginning salary and current salary of 50 randomly selected employees. The correlation between the data sets is r = 0.912. The summary statistics from the data collected are shown bellow: Beginning Salary Ending Salary Mean x¯=56,340 y¯=82,070 Standard deviation Sx = 5,470 Sy = 7,800 Use a complete sentence to describe the strength and direction of the linear relationship between beginning salary and current salary. Find the equation of the least-squares regression line. (Round to two decimal places)
The table below lists measured amounts of redshift and the distances (billions of light-years) to randomly selected astronomical objects. There is sufficient evidence to support a claim of a linear correlation, so it is reasonable to use the regression equation when making predictions. For the prediction interval, use a 90% confidence level with a redshift of 0.0126. Find the explained variation. Redshift Distance OA, 0.157904 OB. 0.444904 OC. 0.000582 OD. 0.219582 0.0231 0.34 0.0536 0.76 0.0715 0.99 0.0391 0.56 0.0438 0.63 0.0109 0.15
The maximum weights (in kilograms) for which one repetition of a half-squat can be performed and the jump heights (in centimeters) for 12 international soccer players are given in the accompanying table. The correlation coefficient, rounded to three decimal places, is r=0.692. At a =0.05, is there enough evidence to conclude that there is a significant linear correlation between the variables? E Click the icon to view the soccer player data. Determine the null and alternative hypotheses. Ho: p o Maximum Weights and Jump Heights Ha: p o Maximum Jump height, y Determine the critical value(s). weight, x 190 60 to = (Round to three decimal places as needed. Use a comma to separate answers as needed.) 185 56 155 55 Determine the standardized test statistic. 180 59 175 55 t= (Round to three decimal places as needed.) 170 65 What is the conclusion? 150 52 160 52 Ho. There V enough evidence at the 5% level of significance to conclude that there is a significant linear correlation between the…
a) Compute the value of the sample correlation coefficient, r. (Round your answer to four decimal places.) r = b) Calculate the test statistic and determine the P-value. (Round your test statistic to one decimal place and your P-value to three decimal places.) t = P- value = c) If a regression analysis were to be carried out to predict endurance from lactate level, what proportion of observed variation in endurance could be attributed to the approximate linear relationship? Answer the question without doing any regression calculations. (Round your answer to four decimal places.) ____________ d) If a regression analysis were to be carried out to predict lactate level from endurance, what proportion of observed variation in endurance could be attributed to the approximate linear relationship? Answer the question without doing any regression calculations. (Round your answer to four decimal places.) _____________
Can you please check my work
A set of n=15 pairs of scores (x and y values) has Ssx =200, Ssy=60, and Sp=30.What is the Pearson correlation for these data?
From the graphs displayed, is there evidence to suggest that there is a positive linear relationship between Square Feet and Bathrooms, for the population of real estate represented by this sample? Be sure to provide numeric support in your answer.
Data collected from a sample of 8 students relating study time (x in hours per week) and leisure time (y in hours per week) yielded the information shown below. What is the value of the sample correlation coefficient? Enter your answer accurate to TWO (2) decimal places. X= 59.37 Y = 4.25 SS= 1843.87 SS, = -49.75 SS, = 7.5
8
Consider a certain data set on shoulder girth and height of a group of individuals. The mean shoulder girth is 107.20 cm with a standard deviation of 10.37 cm. The mean height is 171.14 cm with a standard deviation of 9.41 cm. The correlation between height and shoulder girth is 0.67. Calculate R2 of the regression line for predicting height from shoulder girth, and interpret it in the context of the application.

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