For the 25 year old above with just a college degree, whose mother had a college degree calculate the probability of being employed, enter the probability to three decimal places. **Transcription for Educational Website:**---**Title:** Investigating the Impact of Education on Employment Status Using Logistic Regression**Introduction:**Researchers conducted a study to evaluate how educational attainment influences employment status. The study focused on different levels of education, the education level of the mother, and age. The logistic regression model was utilized to analyze these variables in relation to employment status (yes/no).**Variables Considered:**1. **Education Level:** - \( E1 = 1 \) if the individual has a college degree or higher - \( E2 = 1 \) if the individual has a Master's degree or higher - \( E1 = E2 = 0 \) if the individual has less than a college degree2. **Mother's Education Level:** - \( M = 1 \) if the mother has a college degree or higher - \( M = 0 \) otherwise3. **Age:** - \( A \) is a continuous variable representing the individual's age in years**Logistic Regression Model:**The logistic regression model used is as follows:\[ \text{Logit} = a + B1 \ast E1 + B2 \ast E2 + B3 \ast A + B4 \ast M + B5 \ast A \ast M \]**Estimates Derived Using SAS:**The SAS software provided the following estimates for the coefficients:- Constant term (\(a\)) = -2- Coefficient for \(E1\) (\(B1\)) = 0.2- Coefficient for \(E2\) (\(B2\)) = 0.4- Coefficient for age (\(A\)) (\(B3\)) = 0.1- Coefficient for mother's education (\(M\)) (\(B4\)) = 0.3- Interaction term (Age \(\times\) Mother’s education) (\(B5\)) = 0.02**Conclusion:**This logistic regression model analyzes the potential impact of individual and maternal education levels, alongside age, on the likelihood of being employed. By understanding these dynamics, policymakers and educators can better address employment-related challenges.---

The provided information is as follows:The effect of education is E1 is 1 if the individual has a…

Investigators evaluated the effect of education (E1=1 if college or more, E2=1 if Masters degree or more, E1-E2=0 if less than college), Mother's Education (M=1 if college or more, O otherwise), and age (A, continuous, in years) on employment status (yes/no) using the following Logistic regression model: Logit= a + B1 E1+B2*E2 + B3 A + B4*M + B5*A*M SAS was used to create the following estimates: a= -2, B1-0.2, B2-0.4, B3-0.1, B4-0.3, B5=0.02.

Investigators evaluated the effect of education (E1=1 if college or more, E2=1 if Masters degree or more, E1-E2=0 if less than college), Mother's Education (M=1 if college or more, O otherwise), and age (A, continuous, in years) on employment status (yes/no) using the following Logistic regression model: Logit= a + B1 E1+B2E2 + B3 A + B4M + B5AM SAS was used to create the following estimates: a= -2, B1-0.2, B2-0.4, B3-0.1, B4-0.3, B5=0.02.

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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