Which one of the following statements is true?The correlation coefficient is not affected by outliers.O In the context of correlation and regression, as long as the correlation is strong, it's okay to infer that theexplanatory variable causes the response variable.O The "P" in P-value stands for "practical."O The slope in a regression equation tells us what we predict y to be if x is equal to 0O It is not necessary to know the population size in order to compute the standard deviation of the samplingdistribution.

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Answered: Which one of the following statements…

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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Use the value of the linear correlation coefficient to calculate the coefficient of determination. What does this tell you about the explained variation of the data about the regression line? About the unexplained variation? r= 0.495 Calculate the coefficient of determination. (Round to three decimal places as needed.) What does this tell you about the explained variation of the data about the regression line? % of the variation can be explained by the regression line. (Round to one decimal place as needed.) About the unexplained variation? % of the variation is unexplained and is due to other factors or to sampling error. (Round to one decimal place as needed.)
Measles and Mumps The data show the number of cases of measles and mumps for a recent -year period. + Measles Cases 48 145 64 57 217 Mumps Cases S07 432 1957 2553 379 Send data to Excel The correlation coefficient for the data is 7=-0.688 and a = 0.05. Should regression analysis be done? The regression analysis should not be done. O The regression analysis should be done. Find the equation of the regression line. Round the coefficients to at least three decimal places. y =a= bx a = Given a year with 171 cases of measles, predict the expected number of cases of mumps for that year. Round your answer to at least one decimal place. The number of cases of mumps for that year is
The percentage of the variation in the value of y this is explained by the lease squares regression line is Group of answer choices ρ the slope of the regression line. the correlation coefficient. the coefficient of determination. the y-intercept of the regression line. The data below shows the summary statistics for a regression analysis on car weight (in metric tons) and fuel consumption (in miles per gallon). b0=48.8b0=48.8 b1=−8.37b1=−8.37 r2=0.36r2=0.36 (Note that 0.362=0.13 and 0.36−−−−√=0.6)(Note that 0.362=0.13 and 0.36=0.6) Choose the correct interpretation of the y-intercept of the line:
Which one of the following statements is true? When predicting one quantitative variable based on another, the variable you are trying to predict should always go on the x-axis of the scatterplot. The intercept in a regression equation can never negative. The correlation coefficient has no units. A very strong relationship between variables can result in a value of r that is larger than 1. A correlation coefficient can only range in value from 0 to 1.
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Forest Fires and Acres Burned Numbers (in thousands) of forest fires over the year and the number (in hundred thousands) of acres burned for 7 recent years are shown. Number of fires x 58 47 84 62 57 72 69 Number of acres burned y 54 43 80 58 53 68 65 The correlation coefficient for the data is =r1 and =α0.05 . Should regression analysis be done? The regression analysis should not be done. The regression analysis should be done. Find the equation of the regression line. =y′+abx =a =b Find y′ when =x50 . =y′
K Fit a regression line to the data shown in the chart, and find the coefficient of correlation for the line. Use the regression line to predict life expectancy in the year 2000, where x is the number of decades after 1900. year, x 0 (1900) life expectancy, y 49.1 years 51.4 years 2 (1920) 4 (1940) 53.0 years 6 (1960) 54.2 years 55.2 years 8 (1980) Choose the regression line. OA. y = 0.750x - 49.58 O C. y = 0.750x + 49.58 OB. y=49.58x + 0.750 = 49.58 ○ D. y = The life expectancy in the year 2000, rounded to one decimal place is years.
Tall Buildings The stories and heights (in feet) of a sample of 10 buildings in Pittsburgh are shown. Stories.x 64 54 40 31 45 44 42 41 39 40 Height y 741 625 535 516 515 482 435 420 411 385 Send data to Excel The correlation coefficient for the data is r= 0.788 and a= 0.05. Should regression analysis be done? O The regression analysis should not be done. O The regression analysis should be done. Find the equation of the regression line. Round the coefficients to at least three decimal places. y'=a+bx a = b = Find y' when x = 36. Round your answer to at least three decimal places. y'
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Forest Fires and Acres Burned Numbers (in thousands) of forest fires over the year and the number (in hundred thousands) of acres burned for 6 recent years are shown. Number of fires x 69 58 62 84 47 72 Number of acres burned y 62 42 19 15 26 42 Send data to Excel The correlation coefficient for the data is =r−0.054 and =α0.01 . Should regression analysis be done? The regression analysis should not be done. The regression analysis should be done. Find the equation of the regression line. =y′+abx =a =b Find y′ when =x60 . =y′
n 19 As a general rule it can be stated that: A. Association and causation are two terms that mean the same thing as regression-correlation analysis. B. Correlation shows association but does not prove causation. C. Regression analysis shows causation and correlation analysis proves causation. D. All of the above are correct.
The correlation coefficient r is a measure of how well a regression line fits data. The value of r is always between −1 and 1. If the fit is exact, the value of r is 1 or −1. Values of r near zero indicate a poor fit. Most calculators can be set to display the correlation coefficient.†For the following data set, do the following. x 2 4 6 8 10 y 6 10 22 18 24 Get the regression line. y = Plot the data and the regression line on the same screen. Report the value of the correlation coefficient. (Round your answer to two decimal places.) r =

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