A blood pressure measurement consists of two numbers: the systolic pressure, which is themaximum pressure taken when the heart is contracting, and the diastolic pressure, which isthe minimum pressure taken at the beginning of the heartbeat. Blood pressures weremeasured, in mmHg for a sample of 16 adults. The following table presents the results.Systolic134Diastolic871158311377123771196911888130761167013391112751077111074108691056615710315494Construct a scatterplot of diastolic pressure (y) versus systolic pressure (x) Verify thata linear model is appropriate.a.b. Compute the least-squares line for predicting the diastolic pressure from the systolicpressure.If the systolic pressures of two patients differ by 10 mmHg, by how much would youpredict their diastolic pressures to differ?Predict the diastolic pressure for a patient whose systolic pressure is 125 mmHg.C.d.

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Answered: A blood pressure measurement consists…

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 study is made for a particular allergy medication in order to determine the length of relief it provides Y (in hours) in relation to the dosage of medication X (in mg). For this reason, ten patients were given different doses of the medication and were asked to report back when the medication seemed to wear off. Patient #1 #2 #3 #4 #5 #6 #7 #8 #9 #10 Dosage (x) Relief Hours (y) 3 3.5 4 5 6 6.5 7 8 8.5 9 9.1 5.5 12.3 9.2 14.2 16.8 22.0 18.3 24.5 22.7 (i) Draw a scatter diagram. (ii) Calculate the product moment correlation coefficient and comment on your answer. (iii) Construct the least squares regression line.
Determine the best (according to sum-of-squares-measure) curve y = Aebx , through the data above. Transformed equation ln(y) = ln(A) + bx or Y = a + bx.
Given are five observations for two variables, x and y. xi 1 2 3 4 5 yi 4 6 6 11 13 Develop the estimated regression equation by computing the values of b0 and b1 using b1 = Σ(xi − x)(yi − y) Σ(xi − x)2 and b0 = y − b1x. ŷ = (e) Use the estimated regression equation to predict the value of y when x = 2.
Given are five observations for two variables, x and y. xi 1 2 3 4 5 yi 4 6 5 9 14 Develop the estimated regression equation by computing the the slope and the y intercept of the estimated regression line (to 1 decimal). y^= + x Use the estimated regression equation to predict the value of y when x = 5 (to 1 decimal).y^ =
Given are five observations for two variables, x and y. xi 3 12 6 20 14 yi 55 45 50 15 20 #1) Develop the estimated regression equation by computing the values of b0 and b1 using b1 = Σ(xi − x)(yi − y) Σ(xi − x)2 and b0 = y − b1x. y= #2) Use the estimated regression equation to predict the value of y when x = 13.
#b. Develop an estimated regression equation with both television advertising and newspaper advertising as the independent variables (to 2 decimals).
The variables in our dataset include the college grade point average (colGPA), high school GPA (hsGPA), and achievement test score (ACT) for a sample of 141 students from a large university; both college and high school GPAs are on a four- point scale. We estimate the following model by OLS: colGPA=β₁+β₂hsGPA+β₃ACT+u,and obtain the following parameter estimates β₁=1, β₂=0.5, and β₃=0.02. Predict difference of college GPA's of two students (colGPAB-colGPAA) where the student B has a 0.4 higher GPA in high school and 5 points higher ACT score compared to student A.
The data given below indicate the existence of a linear relationship between the x and y variables. Suppose an analyst who prepared the solutions and carried out the RI measurements was not skilled and as a result of poor technique, allowed intermediate errors to appear. The results are the following:Concentration of solution in percent (x) 10 26 33 50 61Refractive indices (y) 1.497 1.493 1.485 1.478 1.477Step 1. Carefully plot the given x and y values (from the table) on a regular graphing paper. Label then connect the points to observe a zigzag plot due to the scattered points. Step 2: Copy and fill the table given below: x (x - x̄) (x - x̄) 2 y (y - ȳ) (y - ȳ) 2 (x - x̄) (y - ȳ) 10 1.497 26 1.49333 1.48550 1.47861 1.477∑ = ∑ = ∑ = ∑ = ∑ = ∑ = ∑ =x̄= ∑xi ÷ Nx̄= ȳ = ∑yi ÷ Nȳ = Step 3. After completing the table, present following computations and the interpretation.a. Calculate the correlation coefficient (r), using the working formula: r =Σ (x − x ) (y − ȳ)√(Σ(x − x )2)(Σ(y −…
Accountants at the Tucson firm, Larry Youdelman,CPAs, believed that several traveling executives were submittingunusually high travel vouchers when they returned from businesstrips. First, they took a sample of 200 vouchers submitted from the past year. Then they developed the following multiple-regres-sion equation relating expected travel cost to number of days on the road ( x1 ) and distance traveled ( x2 ) in miles:yn = +90.00 + +48.50x1 + +.40x2The coefficient of correlation computed was .68.a) If Donna Battista returns from a 300-mile trip that took herout of town for 5 days, what is the expected amount she shouldclaim as expenses?b) Battista submitted a reimbursement request for $685. Whatshould the accountant do?c) Should any other variables be included? Which ones? Why?
Is at least one of the two variables (weight and horsepower) significant in the model?
For these (x,y) pairs of data points: 1,5 3,7 4,6 5,8 7,9 Compute . Compute . What is the equation of the regression line?
If Elliot collects data from a single sample and her dependent variable is assessed on a nominal scale, which of these difference tests would Elliot need to use to analyze her data? a. single sample t test b. between-subjects, one-way ANOVA. c. chi square goodness of fit test d. single-sample z test

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