Given: A regression of the logarithm of average hourly earnings, ln(wage) on educ, exper, exper2, female, married and numdep.Question: What is the statistical significance of each of the slope coefficients and interpret the coefficient on female and married. SUMMARY OUTPUTRegression StatisticsMultiple RR SquareAdjusted R S 0.39799330.636296610.40487338Standard Erre 0.41241565Observations526ANOVAdfSignificance FMSFRegression6 60.0547654 10.0091276 58.84721921.832E-55Residual519 88.2749818 0.17008667Total525 148.329747Coefficients Standard Ero.t StatP-valueLower 95%Upper 95% Lower 95.0% Upper 95.0%Intercepteduc0.44881563 0.10875487 4.12685549 4.2837E-05 0.235161760.6624695 0.235161760.66246950.07927285 0.0073812610.739746 1.9661E-24 0.06477203 0.09377366 0.06477203 0.093773660.03744652 0.00535391 6.99423735 8.2538E-12 0.02692852 0.04796452 0.02692852 0.04796452experfemale-0.3269239 0.03664357 -B.9217245 7.8791E-18 -0.3989118 -0.2549359 -0.3989118 -0.2549359married0.07429063 0.04251718 1.74730847 0.08117529 -0.0092363 0.15781756-0.0092363 0.15781756numdep-0.0236916 0.01580663 -1.4988368 0.13452396 -0.0547444 0.00736128-0.0547444 0.00736128exper^2-0.0006812 0.00011741 -5.8018953 1.1414E-08 -0.0009119 -0.0004505-0.0009119-0.0004505

Given: A regression of the logarithm of average hourly earnings, ln(wage) on educ, exper, exper2, female, married and numdep. Question: What is the statistical significance of each of the slope coefficients and interpret the coefficient on female and married.

Given: A regression of the logarithm of average hourly earnings, ln(wage) on educ, exper, exper2, female, married and numdep. Question: What is the statistical significance of each of the slope coefficients and interpret the coefficient on female and married.

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter4: Equations Of Linear Functions

Section: Chapter Questions

Problem 6SGR

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Concept explainers

Correlation

Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.

Linear Correlation

A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.

Regression Analysis

Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.

Question

Given: A regression of the logarithm of average hourly earnings, ln(wage) on educ, exper, exper2, female, married and numdep.

Question: What is the statistical significance of each of the slope coefficients and interpret the coefficient on female and married.

SUMMARY OUTPUT
Regression Statistics
Multiple R
R Square
Adjusted R S 0.3979933
0.63629661
0.40487338
Standard Erre 0.41241565
Observations
526
ANOVA
df
Significance F
MS
F
Regression
6 60.0547654 10.0091276 58.8472192
1.832E-55
Residual
519 88.2749818 0.17008667
Total
525 148.329747
Coefficients Standard Ero.
t Stat
P-value
Lower 95%
Upper 95% Lower 95.0% Upper 95.0%
Intercept
educ
0.44881563 0.10875487 4.12685549 4.2837E-05 0.23516176
0.6624695 0.23516176
0.6624695
0.07927285 0.00738126
10.739746 1.9661E-24 0.06477203 0.09377366 0.06477203 0.09377366
0.03744652 0.00535391 6.99423735 8.2538E-12 0.02692852 0.04796452 0.02692852 0.04796452
exper
female
-0.3269239 0.03664357 -B.9217245 7.8791E-18 -0.3989118 -0.2549359 -0.3989118 -0.2549359
married
0.07429063 0.04251718 1.74730847 0.08117529 -0.0092363 0.15781756
-0.0092363 0.15781756
numdep
-0.0236916 0.01580663 -1.4988368 0.13452396 -0.0547444 0.00736128
-0.0547444 0.00736128
exper^2
-0.0006812 0.00011741 -5.8018953 1.1414E-08 -0.0009119 -0.0004505
-0.0009119
-0.0004505

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