. Is the male–female earnings difference estimated from this regressionstatistically significant at the 5% level? Construct a 95% confidenceinterval for the difference. Results of Regressions of Average Hourly Earnings on Gender and Education BinaryVariables and Other Characteristics Using 2012 Data from the Current Population SurveyDependent variable: average hourly earnings (AHE).Regressor(1)(2)(3)College (X1)8.31(0.23)8.32(0.22)8.34(0.22)Female (X2)-3.85(0.23)-3.81(0.22)-3.80(0.22)0.51(0.04)0.52(0.04)Age (X3)0.18(0.36)Northeast (X4)-1.23(0.31)Midwest (Xs)-0.43(0.30)South (X6)17.02(0.17)1.87(1.18)2.05(1.18)InterceptSummary Statistics and Joint Tests7.38F-statistic for regional effects = 09.799.689.67SER0.1620.1800.182R2744074407440

Answered: Is the male–female earnings difference…

Is the male–female earnings difference estimated from this regression statistically significant at the 5% level? Construct a 95% confidence interval for the difference.

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

Use the Financial database from “Excel Databases.xls” on Blackboard. Use Total Revenues, Total Assets, Return on Equity, Earnings Per Share, Average Yield, and Dividends Per Share to predict the average P/E ratio for a company. Use Excel to perform a forward selection regression analysis. Assume a 5% level of significance. Which independent variables are in the final model? Select all that apply. Company Type Total Revenues Total Assets Return on Equity Earnings per Share Average Yield Dividends per Share Average P/E Ratio AFLAC 6 7251 29454 17.1 2.08 0.9 0.22 11.5 Albertson's 4 14690 5219 21.4 2.08 1.6 0.63 19 Allstate 6 20106 80918 20.1 3.56 1 0.36 10.6 Amerada Hess 7 8340 7935 0.2 0.08 1.1 0.6 698.3 American General 6 3362 80620 7.1 2.19 3 1.4 21.2 American Stores 4 19139 8536 12.2 1.01 1.4 0.34 23.5 Amoco 7 36287 32489 16.7 2.76 3.1 1.4 16.1 Arco Chemical 2 3995 4116 6.2 1.14 6.1 2.8 40.4 Ashland 7 14319 7777 9.5 3.8 2.3 1.1 12.4 Atlantic Richfield 7…
A rural state wants to encourage high school graduates to continue their education and attend college. The state collected information on a random sample of high school seniors from across the state 7 years ago and is now observing how many years of education they completed. They believe students decide to achieve more education when they are more capable, have easier access to college education, and the opportunity cost of attending are lower. To explore the factors that affect the years of education completed they have used multiple regression to estimate the years of completed education as a function of: Unemployment rate - the unemployment rate in the county (3.9 – 16.8) County Hr Wage - average starting hourly manufacturing wage in the county Test - student score on college admission test (0 to 100 scale) Dist to college - Distance to near college (measured in 100’s of miles) Tuition - Tuition charged at nearest state university (measured in $1000s)…
You plan to fit a regression model that will be used to predict first-year college GPA (FYGPA) from high-school GPA (HSGPA), ACT score (ACT), first-generation status (Yes or No), socioeconomic class (lower class, lower to middle class, middle to upper class, and upper class), and school type (public or private). What is the total number of estimated regression coefficients? If the sample size is n = 250 students, what are the degrees of freedom for the following sources of variation: Regression Error Total
1. Find the p-value. (Round to three or more decimal places.) 2. At the 0.01 level of significance, can the doctor conclude that the mean recovery time of patients who have the new procedure is less than the mean recovery time of patients who have the standard procedure?