The following data give the hardness (X) andFindtensile strength (Y) of 7 samples of a metal in certain units.the linear regression equation Y on X.146152158164170176182X :Y :75787779828586

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Answered: The following data give the hardness…

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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The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 40 inches. Is the result close to the actual weight of 352 pounds? Use a significance level of 0.05. Chest size (inches) *Weight (pounds) 44 54 328 528 41 55 39 51 418 580 296 503 Click the icon to view the critical values of the Pearson correlation coefficient r. - What is the regression equation? x (Round to one decimal place as needed.)
Height, x 772 628 518 508 496 483 stories, y 51 48 44 43 37 35 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 table below shows the heights (in feet) and the number of stories of six notable buildings in a city. (a) x = 498 feet (b) x = 640 feet (c) x = 345 feet (d) 735 feet Find the regression equation.Now construct a scatter plot of the data and draw the regression line. (a) Now use the regression equation to predict the value of y for each of the given x-values, if meaningful. Because the correlation between x and y is significant, the equation of the regression line can be used to predict y-values. However, prediction values are meaningful only for x-values in the range of the data. Begin with x = 498. Since x = 498…
Fit a linear regression model for the following data.
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 0 1 3 4 5 6 (a) x=3 hours (b) x=2.5 hours Test score, y 40 44 52 49 62 70 (c) x=15 hours (d) x=1.5 hours Question content area bottom Part 1 Find the regression equation. y=enter your response herex+enter your response here (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.)
The ages (in years) of five men and their systolic pressures. (You can use technology) Age, x 16 25 39 45 49 Systolic blood pressure, y 109 122 143 132 199 a. calculate the correlation coefficient, r b. calculate the critical r c. Is there a significant linear relationship between x and y? d. find the equation of regression line e Interpret the slope and the y-intercept f. Predict the systolic blood pressure for a man who is 40 years old.
An unknown metal has been found and the following experimental results have been tabulated in the table below. The table contains the grams of the unknown metal and the volume in milliliters of water displacement. Find a linear model that expresses mass as a function of the volume. grams Volume in ml 17 174.8 19.5 208.6 22 230.8 24.5 257 27 280.4 29.5 312.5 32 329 A) Write the linear regression equation for the data in the chart. Volume x + where x is the grams of the unknown metal. Round your answers to 3 decimal places B) If the mass of an unknown metal is 15, using your un-rounded regression equation find its predicted volume. Round your answer to 1 decimal place. mL
Annual high temperatures in a certain location have been tracked for several years. Let X represent the number of years after 2000 and Y the high temperature. Based on the data shown below, calculate the linear regression equation using technology (each constant to 2 decimal places). x y 4 36.68 5 35.85 6 35.52 7 35.99 8 38.46 9 38.93 10 38 11 38.07 12 39.54 13 40.11 14 41.58 The equation is y^ = x + Interpret the slope For each additional 33.38 years, the annual high temperature will increase by 1 degree on average. For each additional 0.52 years, the annual high temperature will increase by 1 degree on average. For each additional year, the annual high temperature will increase by 0.52 degrees on average. For each additional year, the annual high temperature will increase by 33.38 degrees on average. Interpret the y-intercept In 2000, the temperature was about 33.38. It does not make sense to interpret the intercept in this scenario. In 2004, the…
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 Test score, y 4 (a) x = 2 hours (c) x = 13 hours (b) x= 2.5 hours (d) x = 4.5 hours 2 3 5 40 45 52 49 63 70 Find the regression equation. ý =x+ (O (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.) Choose the correct graph below. O A. OB. OC. OD. 80- 80- Hours studying Hours studying Hours studying Hours studying (a) Predict the value of y for x= 2. Choose the correct answer below. O A. 52.2 О В. 49.2 ОС. 64.2 O D. not meaningful (b) Predict the value of y for x = 2.5. Choose the correct answer below. O A. 115.4 О В. 52.2…
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 valuo of v for each of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of six notable buildings in a city. Height, x Stories, y 762 621 508 480 (b) x = 641 feet (d) x = 726 feet 515 491 (a) x= 498 feet (c) x = 810 feet 51 46 44 42 38 37 Find the regression equation. ý=x+ (D (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.) Choose the correct graph below. OA. OB O B. Oc. OD. 60- 604 60+ 800 B00 G 800 Height (feet) 800 Height (feet) 800 Height (feet) Height (feet) (a) Predict the value of y for x = 498. Choose the correct answer below. OA 40 ОВ. 50 O C. 47 O D. not meaningful (b) Predict the value of y for x 641. Choose the correct answer…
The following table shows students’ number of absences, x, and the student’s final grade,, y.# of absences x 6 2 15 9 12 5 8 Final grade y 82 86 43 74 58 90 78a) Calculate r, the correlation coefficient ________________b) Find the equation of the regression line __________________________________c) If a student is absent 4 times,, what grade does your regression line predict?__________________
An unknown metal has been found and the following experimental results have been tabulated in the table below. The table contains the grams of the unknown metal and the volume in milliliters of water displacement. Find a linear model that expresses mass as a function of the volume. grams Volume in ml 15 205.9 16.5 224.3 18 244.7 19.5 267.7 21 279.7 22.5 312 24 326.2 A) Write the linear regression equation for the data in the chart. Volume where x is the grams of the unknown metal. Round your answers to 3 decimal places B) If the mass of an unknown metal is 13, using your un-rounded regression equation find its predicted mL volume. Round your answer to 1 decimal place.
Grades on Midterm Grades on Final79 8464 7676 8385 9170 7586 7960 7975 8781 8263 63 The following table gives the data for the grades on the midterm exam and the grades on the final exam. Determine the equation of the regression line, yˆ=b0+b1x . Round the slope and y-intercept to the nearest thousandth.

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The following data give the hardness (X) and Find tensile strength (Y) of 7 samples of a metal in certain units. the linear regression equation Y on X. 146 152 158 164 170 176 182 х : Y : 75 78 77 79 82 85 86