A medical research study is interested in predicting the blood pressure (in mmHg) for subjectsexposed to noise at various volumes (in decibels). A least-squares regression line was fit to datacollected from 20 subjects who were randomly assigned to receive a certain noise exposure level.The equation of the line isŷ = -10+ 0.20xwhere x is noise exposure and ŷ is the predicted blood pressure. Which of the following gives thebest interpretation of the slope of the least-squares regression line?(A) There is an increase of 0.20 mmHG in the predicted blood pressure of a subject for everyincrease of 1 decibel in noise exposure volume.(B) There is an increase of 0.20 decibels in the predicted noise exposure volume of a subject forevery increase of 1 mmHg in blood pressure.(C) There is a decrease of 10 mmHG in the predicted blood pressure of a subject for every increaseof 1 decibel in noise exposure volume.(D) There is a decrease of 10 decibels in the predicted noise exposure volume of a subject for everyincrease of 1 mmHg in blood pressure.(E) Approximately 20% of the variability in blood pressure is predicted by its linear relationshipwith noise exposure volume.

In the given regression equation, y = -10 + 0.20x, y represents the predicted blood pressure and x…

Answered: A medical research study is interested…

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 researcher interested in explaining the level of foreign reserves for the country of Barbados estimated the following multiple regression model using yearly data spanning the period 2001 to 2016: FR=a+B0IL+YEXP+8FDI Where FR = yearly foreign reserves ($000°s), OIL = annual oil prices, EXP = yearly total exports ($000's) and FDI = annual foreign direct investment ($000`s). The sample of data was processed using MINITAB and the following is an extract of the output obtained: Predictor Coef StDev t-ratio p-value Constant 5491.38 2508.81 2.1888 0.0491 OIL 85.39 18.46 4.626 0.0006 EXP -377.08 112.19 0.0057 FDI -396.99 160.66 -2.471 ** s = 2.45 R-sq = 96.3% R-sq (adj) = 95.3% Analysis of Variance Source DF MS F Regression 1991.31 663.77 ?? Error 12 77.4 6.45 Total 15 d) Hence test whether ß is significant. Give reasons for your answer. e) Perform the F Test making sure to state the null and alternative hypothesis. f) Given an interpretation of the term “R-sq“ and comment on its value.
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