D: Applied Statistics home > 3.1: Interpreting fitted modelsE zyBooksA medical researcher wants to determine how a new medication affects blood pressure.150The equation of the regression line isÝ = 140 + (-0.0667)X.140An amount of medication of 195 mgis found to result in a blood pressureof 124.39 mm Hg. What is the130120predicted blood pressure?Ex: 7.9mm Hg110Where is the observed value inrelation to the regression line?10050100150200250Pick300350Amount of medication (in mg)An amount of medication of 173 mg is found to result in ablood pressure of 128.46 mm Hg. What is the predicted blood pressure?Where is the observed value in relation to the regression line?mm HgPickAn amount of medication of 151 mg is found to result in ablood pressure of 133.73 mm Hg. What is the predicted blood pressure?Where is the observed value in relation to the regression line?mm HgPickCheckNextPatient systolic blood pressure (in mm Hg)

Given dataA new medical researcher wants to determine how a new medicationaffects blood pressure

Answered: 150 The equation of the regression line…

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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A regression was run to determine if there is a relationship between hours of study per week (x) and the final exam Scores (y). The results of the regression were: y=ax+b a=6.179 b=28.96 r²=0.937024 r=0.968 Use this to predict the final exam score of a student who studies 4 hours per week, and please round your answer to a whole number.
Find the regression equation Student 1 4 5 6 7 8 9 10 Placement Exam 83 89 92 77 81 81 85 85 87 84 GWA 83 85 90 80 83 85 87 84 90 85 Select the correct response: y=35.39-0.5901x y=35.39x+0.5901 y=0.5901x-35.39 y=35.39+0.5901x 3. 2.
Using your dataset, run a regression of Y=GPA and X=# Friends.(do not need your actual data, just the regression results)a) State what this regression is attempting to analyze. “By running this regression, we areattempting to show.....”b) Write out the regression equation and describe what it shows (if Friends increase by 1, then. . . ).c) Find your hypothesized GPA when the # friends equals 17.d) Is the slope of # of Friends significantly different from zero?Include Ho, Ha, decision rule, t statistic from table, tc, decision, and conclusion.e) Is the r-squared of # of Friends significantly different from zero?Include Ho, Ha, decision rule, F statistic from table, Fc, decision, and conclusion.
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: y=ax+b a=-0.794 b=31.311 r²=0.9801 r=-0.99 Use this to predict the number of situps a person who watches 8 hours of TV can do (to one decimal place)
The data show the bug chirps per minute at different temperatures. Find the regression equation, letting the first variable be the independent (x) variable. Find the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute. Use a significance level of 0.05. What is wrong with this predicted value? Chirps in 1 min 924 1150 840 1166 1087 930 Temperature (°F) 77.5 84.6 74.1 91 79.6 79.7 What is the regression equation? What is the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute? What is wrong with this predicted value? Choose the correct answer below. A. It is unrealistically high. The value 3000 is far outside of the range of observed values. B. The first variable should have been the dependent variable. C. It is only an approximation. An unrounded value would be considered accurate. D. Nothing is wrong with this value. It can be…
The linear regression equation for predicting systolic blood pressure from age is: y = 54 + 1.6*x Find the residual for a person who is 32 years of age with a systolic blood pressure of 103.9 (round your answer to one decimal place)
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The slope, b represents * O predicted value of Y when X = 0. O the estimated average change in Y per unit change in X. O variation around the line of regression. O the predicted value of Y.
A regression analysis was performed to determine if there is a relationship between hours of TV watched per day (x) and number of sit ups a person can do (y ). The results of the regression were: y=ax+b a=-1.33 b=25.138 r2=0.712336 r=-0.844 Use this to predict the number of sit ups a person who watches 10 hours of TV can do, and please round your answer to a whole number.
A regression was run to determine if there is a relationship between hours of study per week (xx) and the test scores (yy).The results of the regression were:y=ax+b a=6.686 b=35.26 r2=0.6084 r=0.78 Use this to predict the final exam score of a student who studies 8.5 hours per week, and please round your answer to a whole number.
A regression was run to determine if there is a relationship between hours of study per week (xx) and the final exam scores (yy).The results of the regression were: y=ax+b a=5.614 b=32.79 r2=0.808201 r=0.899 Use this to predict the final exam score of a student who studies 1 hours per week, and please round your answer to a whole number.

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