1.Consider the following regression model:Fram Risk Score; = Bo + B1 × Health Insurance; + u¿The Framingham Risk Score predicts 10-year risk of cardiovascular disease based on age,cholesterol levels, blood pressure, blood sugar, use of medication for high blood pressure, andsmoking. A higher score means worse overall cardiovascular health. A researcher who collectsdata and regresses the Fram Risk Score against Health Insurance (= 1 if have insurance) findsthat B,< 0.The OLS estimator, B, , however, likely suffers from omitted variable bias because those whohave health insurance, on average, tend to be more prudent than those who do not have healthinsurance. Because of this omitted variable bias, it is likely the case that B1 B1.A)В)>2.Consider the following regression model:Class Average; = Bo + B1 x Office Hours; + u;Class Average is the students' average grade in the class at the end of the term and Office Hoursis the number of office hours held by the instructor over the entire term.A researcher who collects data and regresses Class Average against Office Hours finds that,surprisingly, B< 0.The OLS estimator, B1 , however, likely suffers from omitted variable bias because instructorswho teach large introductory courses with many non-major enrollees, in which grades arerelatively low, might hold more office hours than instructors who teach small upper levelcourses with few non-major enrollees, in which grades are relatively high. Because of thisomitted variable bias, it is likely the case that ß1_B1.A)B)<>V AV A

Consider the following regression model: Fram Risk Score; = Bo + B1 × Health Insurance; + u¿ The Framingham Risk Score predicts 10-year risk of cardiovascular disease based on age, cholesterol levels, blood pressure, blood sugar, use of medication for high blood pressure, and smoking. A higher score means worse overall cardiovascular health. A researcher who collects data and regresses the Fram Risk Score against Health Insurance (= 1 if have insurance) finds that B1< 0. The OLS estimator, B1, however, likely suffers from omitted variable bias because those who have health insurance, on average, tend to be more prudent than those who do not have health insurance. Because of this omitted variable bias, it is likely the case that ß1_B1.

Consider the following regression model: Fram Risk Score; = Bo + B1 × Health Insurance; + u¿ The Framingham Risk Score predicts 10-year risk of cardiovascular disease based on age, cholesterol levels, blood pressure, blood sugar, use of medication for high blood pressure, and smoking. A higher score means worse overall cardiovascular health. A researcher who collects data and regresses the Fram Risk Score against Health Insurance (= 1 if have insurance) finds that B1< 0. The OLS estimator, B1, however, likely suffers from omitted variable bias because those who have health insurance, on average, tend to be more prudent than those who do not have health insurance. Because of this omitted variable bias, it is likely the case that ß1_B1.

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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