Measles and Mumps The data show the number of cases of measles and mumps for a recent 5-year period. Measles Cases 41 142 71 61 202 Mumps Cases 817 462 1983 2605 354 Send data to Excel The correlation coefficient for the data is r=-0.647 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 = b = Given a year with 164 cases of measles, predict the expected number of cases of mumps for that year. Round y answer to at least one decimal place. The number of cases of mumps for that year is

Measles and Mumps The data show the number of cases of measles and mumps for a recent 5-year period. Measles Cases 41 142 71 61 202 Mumps Cases 817 462 1983 2605 354 Send data to Excel The correlation coefficient for the data is r=-0.647 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 = b = Given a year with 164 cases of measles, predict the expected number of cases of mumps for that year. Round y answer to at least one decimal place. The number of cases of mumps for that year 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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Prices and mileage of 48 Dodge 2500 Pickup trucks with Cummins diesel engines. Prices ranged from $28,925 to $68,650. Mileage ranged from 315 to 186,466. While I did not share the trucks were 2013 to 2020 models. Please show all work. Interpret b0 in the context of this problem. Interpret b1 in the context of this problem. What percent of total variation in prices is explained by the regression model? Provide evidence to support your answer. Price Mileage 52293 34450 50987 23372 62988 21738 37500 81176 66000 23118 47601 71143 47750 18214 42000 32303 50987 23372 28925 143737 42050 58561 51738 9691 51500 23969 44988 48781 29500 114809 46975 16918 63999 15507 46975 16918 43222 50459 38386 87192 42000 68722 62250 14042 62998 21738 32130 103644 52293 34450 52900 68883 53172 3656 53494 315 39594 88441 63246 23631 58250 34974 59391 18383 50650 42737 54976 84200 68650 14401 51114 47433 43900 74106 37450…
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?
EQuestion Help Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The number of hours 6 students spent for a test and their scores on that test are shown below. Hours spent studying, x IA Test score,y 3 (a) x=2 hours (c) x= 12 hours (b) x = 25 hours (d) x= 4.5 hours 38 44 50 47 61 68 Find the regression equation. y = 6.269 x+ (32.48) (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.) Choose the correct graph below. OD. OB. OC. O A. 80- 80- 80 80-4 0-+ Hours studying Hours studying Hours studying Hours studying 10 18 PM (E) More 10/3/2020 Click to select your answer(s)
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= -0.438 please dont copy paste the content from other sites
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′
Prev The table below gives the list price and the number of bids received for five randomly selected items sold through online auctions. Using this data, consider the equation of the regression line, y = bo + b₁x, for predicting the number of bids an Item will receive based on the list price. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, In practice, It would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Price in Dollars 28 33 36 42 45 Number of Bids 1 7 8 9 10 Step 3 of 6: Find the estimated value of y when x = 33. Round your answer to three decimal places. Table Copy Data Next
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.
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′
Prev The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, y = bo + b₁x, for predicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, In practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Age Bone Density 61 62 68 69 40 357 350 343 340 315 Step 1 of 6: Find the estimated slope. Round your answer to three decimal places. Table Copy Data Next