When a drug is administered to a patient, doctors and nurses must be aware of the minimal effective concentration, which is the concentration below which thedrug doesn't have the desired effect. One way health professionals talk about this concentration is the half-life of elimination, which is the amount of time ittakes for the concentration to be cut in half. The data below is based on theophylline, an antiasthma drug, where the time is the number of hours after themedication peaks and starts to decline in the bloodstream.Time (hrs) Concentration (mg/L)081624Part: 0 / 5Part 1 of 594.52.251.125(a) Many drugs are known to leave the body exponentially. Determine the exponential regression equation of best fit using ExpReg on a graphingcalculator, where y is concentration and x is time. The process for doing this is identical to that for linear and quadratic regression from earlier in thisunit. Round to three decimal places, if necessary.y =

Here dependent variable (y) is concentration.Independent variable (x) is time.Sample size To find…

Answered: (a) Many drugs are known to leave the…

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 linear regression equation for predicting systolic blood pressure from age is: ŷ = 42 + 1.1*x Find the residual for a person who is 36 years of age with a systolic blood pressure of 80.1 (round your answer to one decimal place)
You have a regression equation based on data from years 1 thru 10 (y = 6 + 32x, where x equals year). You want to forecast a result in year 20. How would you do it?
A red maple sapling was 3 feet tall when planted in 2010. Six years later, the tree was 18 feet tall. The growth rate of the tree is constant over time. Find a linear model for the height H (in ft) of the red maple t years after 2010. Let t = 0 represent 2010. H = What is the expected height (in ft) of the red maple in 2020? ft
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=-0.649 b=20.136 r2=0.488601 r=-0.699 Use this to predict the number of situps a person who watches 2.5 hours of TV can do (to one decimal place)
Please only answer “d” and “e” as I already have the other parts filled out. Thank you!
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=-0.649 b=20.136 r2=0.488601 r=-0.699 Use this to predict the number of situps a person who watches 2.5 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? What is the regression equation? (Round the x-coefficient to four decimal places as needed. Round the constant to two decimal places as needed.) What is the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute? The best predicted temperature when a bug is chirping at 3000 chirps per minute is ______ degrees F. (Round to one decimal place as needed.) What is wrong with this predicted value? Choose the correct answer below. A. It is only an approximation. An unrounded value would be considered accurate. B. The first variable should have been the dependent variable. C. It…
1. A retail variety store that advertises extensively by mail circulars expects a sale with 20% probability. Suppose 30 prospects are randomly selected from a city-wide mailing. a. What is the expected number (mean) of sales of this store from this sample of 30? 6 1.5 30 20 Jimmy and Rosalynn Carter celebrate 76 years of marria
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=-1.371 b=36.465 ²0.395641 r=-0.629 Use this to predict the number of situps a person who watches 9 hours of TV can do (to one decimal place)
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=-1.319 b=38.85 r2=0.720801 r=-0.849 Use this to predict the number of situps a person who watches 7.5 hours of TV can do (to one decimal place)
A set of X and Y scores has SSX = 26, SSY = 10, and SP = 42. What is the slope for the regression equation? Round your answer to 2 decimal places.
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=-0.722 b=21.301 r2=0.381924 r=-0.618 Use this to predict the number of situps a person who watches 2 hours of TV can do (to one decimal place)

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