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Let's say that later, the researd substantially increases her sample size to 400,000 observations. variable work experience, she runs the same regression of wage on age, education, and gender. Compared to the model with 4000 observations, the model with this increased in sample size will: Decrease the bias of the estimated coefficient for education, and increase its statistical significance. ODecrease the bias of the estimated coefficient for education, and decrease its statistical significance. ODecrease the bias of the estimated coefficient for education, but not affect its statistical significance. OIncrease the statistical significance of the estimated coefficient for education, but not affect the bias. OAffect neither the statistical significance nor the bias of the estimated coefficient for education.

Let's say that later, the researd substantially increases her sample size to 400,000 observations. variable work experience, she runs the same regression of wage on age, education, and gender. Compared to the model with 4000 observations, the model with this increased in sample size will: Decrease the bias of the estimated coefficient for education, and increase its statistical significance. ODecrease the bias of the estimated coefficient for education, and decrease its statistical significance. ODecrease the bias of the estimated coefficient for education, but not affect its statistical significance. OIncrease the statistical significance of the estimated coefficient for education, but not affect the bias. OAffect neither the statistical significance nor the bias of the estimated coefficient for education.

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter10: Statistics
Section10.6: Summarizing Categorical Data
Problem 35PPS
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Question () A researclher estimates a model on wages using 4000 observations on workers. She includes explanatory variables measuring age, education, and gender. Work experience, which is negatively correlated with education, also affects the wage, but this variable is not included in her data. The coefficient of education in her regression is therefore biased. Let's say that later, the researcher gets a grant to collect more data, and thereby substantially increases her sample size to 400,000 observations. Still lacking the variable work experience, she runs the same regression of wage on age, education, and gender. Compared to the model with 4000 observations, the model with this increased in sample size will: Decrease the bias of the estimated coefficient for education, and increase its statistical significance. Decrease the bias of the estimated coefficient for education, and decrease its statistical significance. ODecrease the bias of the estimated coefficient for education, but not affect its statistical significance. O Increase the statistical significance of the estimated coefficient for education, but not affect the bias. OAffect neither the statistical significance nor the bias of the estimated coefficient for education.
Transcribed Image Text:Question () A researclher estimates a model on wages using 4000 observations on workers. She includes explanatory variables measuring age, education, and gender. Work experience, which is negatively correlated with education, also affects the wage, but this variable is not included in her data. The coefficient of education in her regression is therefore biased. Let's say that later, the researcher gets a grant to collect more data, and thereby substantially increases her sample size to 400,000 observations. Still lacking the variable work experience, she runs the same regression of wage on age, education, and gender. Compared to the model with 4000 observations, the model with this increased in sample size will: Decrease the bias of the estimated coefficient for education, and increase its statistical significance. Decrease the bias of the estimated coefficient for education, and decrease its statistical significance. ODecrease the bias of the estimated coefficient for education, but not affect its statistical significance. O Increase the statistical significance of the estimated coefficient for education, but not affect the bias. OAffect neither the statistical significance nor the bias of the estimated coefficient for education.
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