Obtain the two lines of regression from the following data and estimate theblood pressure when age is 50 years. Can we also estimate the blood pressure of a per-son aged 20 years on the basis of this regression equation ? Discuss.40115Age (in years) : 56Blood Pressure : 127 112 140 118 1294212068135 133604752116 1304272396349125

Answered: Image /qna-images/answer/9371308b-e95a-4f2f-b474-21c39f717da2.jpg

Answered: Obtain the two lines of regression from…

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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Answer the given problem. Process the data in excel and present the results. A researcher is interested in knowing how well he can predict blood pressure from sodium intake. 1. Formulate the regression equation for the data. 2. What would be the likely blood pressure reading for a patient with a sodium intake of 6.0? of 8.5? Patients Sodium BP 1 6.5 151 2 7.3 170 3 6.6 165 4 7.5 172 5 7.6 187 6 6.7 161 7 6.7 169 8 7.8 192 9 7 185 10 7.4 190 T 11 6.2 145 12 6.7 OL 143 R E S6.7
The following data shows the height children with time: Age X, in |(months) Height Y, in ( cm) 18 19 20 21 22 76.1 77.0 78.1 78.2 78.8 The regression equation, correct to 3 decimal place is Drag and drop the correct answer. Y = 0.517X + 55.876 Y = 0.688X + 63.927 Y = 0.635X + 64.928 Y = 0.669X + 62.216 %3D
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 w Click to copy table. a chest size of 58 inches. Is the result close to the actual weight of 632 pounds? Use a significance level of 0.05. Chest size (inches) Weight (pounds) 46 57 53 41 40 40 384 580 542 358 306 320 Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? y = + x (Round to one decimal place as needed.) What is the best predicted weight of a bear with a chest size of 58 inches? The best predicted weight for a bear with a chest size of 58 inches is pounds. (Round to one decimal place as needed.) Is the result close to the actual weight of 632 pounds? A. This result is close to the actual weight of the bear. B. This result is very close to the actual weight of the bear. C. This result is exactly the same as the actual weight of the bear. D.…
Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find the regression equation, letting the right arm blood pressure be the predictor (x) variable. Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 85 mm Hg. Use a significance level of 0.05. Right Arm 100 99 92 80 79 O Left Arm 175 169 182 149 148 E Click the icon to view the critical values of the Pearson correlation coefficient r The regression equation is y =+x. (Round to one decimal place as needed.)
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, y = bo + b₁x. Round the slope and y-intercept to the nearest thousandth. Grades on Midterm and Final Exams Grades on Midterm 75 83 76 75 64 69 89 88 84 62 82 72 76 100 Grades on Final 77 82 73 75 81 63
Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find the regression equation, letting the right arm blood pressure be the predictor (x) variable. Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 85 mm Hg. Use a significance level of 0.05. Right Arm 100 99 91 76 76 5 Left Arm 175 170 146 147 146 Click the icon to view the critical values of the Pearson correlation coefficient r The regression equation is y = +x (Round to one decimal place as needed.) Given that the systolic blood pressure in the right arm is 85 mm Hg, the best predicted systolic blood pressure in the left arm is mm Hg. (Round to one decimal place as needed.)
Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find the regression equation, letting the right arm blood pressure be the predictor (x) variable. Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 80 mm Hg. Use a significance level of 0.05. Right Arm 100 99 91 78 77 D Left Arm 177 171 144 146 146 Data Table Click the icon to view the critical values of the Pearson correlation coefficient r The regression equation is y= Round to one decimal place as needed.) NOTE: To test Ho p= 0 against H,: p±0, reject Ho if the absolute value of r is greater than the critical value in the table. X. a = 0.05 a = 0.01 4. 0.950 0.990 0.878 0.959 0.811 0.917 0.754 0.875 0.834 7 0.707 9. 0.666 0.798 10 0.632 0.765 11 0.602 0.735 12 0.576 0.708 13 0.553 0.684 14 0.532 0.661 15 0.514 0.641 16 0.497 0.623 17 0.482 0.606 18 0.468 0.590 0.456 0.575 0.561 19 20 0.444 25 0.396 0.505 30 0.361…
Interpret the values of the regression coefficients (intercept and slope)in this context. Note whether the intercept is meaningful (valid) for this data set.
For the data below, what is the value of "b" for the regression equation? Family Father Son 120 121 110 105 120 125 92 87 85 92 72 90 107 110 115 122 155 133 90 123
See attached image for the introduction. How much variation in price has been explained by the total number of square feet?
Listed.below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find the regression equation, letting the right arm blood pressure be the predictor (x) variable. Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 1000 mm Hg. Use a significance level of 0.05. Right Arm 102 101 94 79 79 O Left Arm 175 168 146 147 145 Click the icon to view the critical values of the Pearson correlation coefficient r The regression equation is y= X. (Round to one decimal place as needed.)
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 content from other sources

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