Suppose a professor wants to know how the time spent studying affects student performance on microeconomic exams in college. She uses her class as a convenience sample, and she implements a randomized controlled trial by randomly dividing her class into a treatment and a control group to answer this question. Her experimental data contains the number of hours students study per week and their final microeconomics exam scores. If she estimates the following bivariate model using OLS, will her estimates of betao and betal be unbiased? Why or why not? examscore ibeta0-beta1*hrsstudy_i+u_ No, because exam scores are unlikely to be normally distributed. Yes, because she conducted a randomized controlled trial. Yes, because there are unlikely to be outlier observations in exam scores or hours spent studying No, because she didn't collect a random sample from the population of interest. No, because there is likely no relationship between study time and exam scores. Yes, because the OLS estimation method gives the causal effect of X on Y. No, because there are likely omitted variabies in u_i that are correlated with hours spent studying and student exam scores.

MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
icon
Related questions
Question
Suppose a professor wants to know how the time spent studying affects student performance on microeconomic exams in college. She uses her class as a convenience sample, and she implements a randomized controlled trial by randomly
dividing her class into a treatment and a control group to answer this question. Her experimental data contains the number of hours students study per week and their final microeconomics exam scores. If she estimates the following bivariate
model using OLS, will her estimates of beta0 and beta1 be unbiased? Why or why not?
examscore_i=beta0+beta1*hrsstudy_i+u_i
No, because exam scores are unlikely to be normally distributed.
Yes, because she conducted a randomized controlled trial.
Yes, because there are unlikely to be outlier observations in exam scores or hours spent studying.
No, because she didn't collect a random sample from the population of interest.
No, because there is likely no relationship between study time and exam scores.
Yes, because the OLS estimation method gives the causal effect of X on Y.
No, because there are likely omitted variables in u_i that are correlated with hours spent studying and student exam scores.
Transcribed Image Text:Suppose a professor wants to know how the time spent studying affects student performance on microeconomic exams in college. She uses her class as a convenience sample, and she implements a randomized controlled trial by randomly dividing her class into a treatment and a control group to answer this question. Her experimental data contains the number of hours students study per week and their final microeconomics exam scores. If she estimates the following bivariate model using OLS, will her estimates of beta0 and beta1 be unbiased? Why or why not? examscore_i=beta0+beta1*hrsstudy_i+u_i No, because exam scores are unlikely to be normally distributed. Yes, because she conducted a randomized controlled trial. Yes, because there are unlikely to be outlier observations in exam scores or hours spent studying. No, because she didn't collect a random sample from the population of interest. No, because there is likely no relationship between study time and exam scores. Yes, because the OLS estimation method gives the causal effect of X on Y. No, because there are likely omitted variables in u_i that are correlated with hours spent studying and student exam scores.
Suppose a professor wants to know how the time spent studying affects student performance on microeconomic exams. She collects a random sample of observational data on students in 2019. Her data contain the number of hours students
study per week and their final microeconomics exam scores. If she estimates the following bivariate model using OLS, will her estimates of beta0 and beta1 be unbiased? Why or why not?
examscore_i=beta0+beta1+hrsstudy_i+u_i
No, because exam scores are unlikely to be normally distributed.
No, because there are likely omitted variables in u_i that are correlated with hours spent studying and student exam scores.
Yes, because she collected a random sample.
Yes, because the OLS estimation method gives the causal effect of X on Y.
Yes, because there are unlikely to be outlier observations in exam scores or hours spent studying.
No, because there is likely to be no relationship between studying and exam scores.
Transcribed Image Text:Suppose a professor wants to know how the time spent studying affects student performance on microeconomic exams. She collects a random sample of observational data on students in 2019. Her data contain the number of hours students study per week and their final microeconomics exam scores. If she estimates the following bivariate model using OLS, will her estimates of beta0 and beta1 be unbiased? Why or why not? examscore_i=beta0+beta1+hrsstudy_i+u_i No, because exam scores are unlikely to be normally distributed. No, because there are likely omitted variables in u_i that are correlated with hours spent studying and student exam scores. Yes, because she collected a random sample. Yes, because the OLS estimation method gives the causal effect of X on Y. Yes, because there are unlikely to be outlier observations in exam scores or hours spent studying. No, because there is likely to be no relationship between studying and exam scores.
Expert Solution
trending now

Trending now

This is a popular solution!

steps

Step by step

Solved in 2 steps

Blurred answer
Similar questions
  • SEE MORE QUESTIONS
Recommended textbooks for you
MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
Statistics
ISBN:
9781119256830
Author:
Amos Gilat
Publisher:
John Wiley & Sons Inc
Probability and Statistics for Engineering and th…
Probability and Statistics for Engineering and th…
Statistics
ISBN:
9781305251809
Author:
Jay L. Devore
Publisher:
Cengage Learning
Statistics for The Behavioral Sciences (MindTap C…
Statistics for The Behavioral Sciences (MindTap C…
Statistics
ISBN:
9781305504912
Author:
Frederick J Gravetter, Larry B. Wallnau
Publisher:
Cengage Learning
Elementary Statistics: Picturing the World (7th E…
Elementary Statistics: Picturing the World (7th E…
Statistics
ISBN:
9780134683416
Author:
Ron Larson, Betsy Farber
Publisher:
PEARSON
The Basic Practice of Statistics
The Basic Practice of Statistics
Statistics
ISBN:
9781319042578
Author:
David S. Moore, William I. Notz, Michael A. Fligner
Publisher:
W. H. Freeman
Introduction to the Practice of Statistics
Introduction to the Practice of Statistics
Statistics
ISBN:
9781319013387
Author:
David S. Moore, George P. McCabe, Bruce A. Craig
Publisher:
W. H. Freeman