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To Examine the Differences Between Salaries of Male and Female

question 89

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To examine the differences between salaries of male and female middle managers of a large bank, 90 individuals were randomly selected, and two models were created with the following variables considered: Salary = the monthly salary (excluding fringe benefits and bonuses) ,
Educ = the number of years of education,
Exper = the number of months of experience,
Train = the number of weeks of training,
Gender = the gender of an individual; 1 for males, and 0 for females.
Excel partial outputs corresponding to these models are available and shown below.
Model A: Salary = β0 + β1Educ + β2Exper + β3Train + β4Gender + ε To examine the differences between salaries of male and female middle managers of a large bank, 90 individuals were randomly selected, and two models were created with the following variables considered: Salary = the monthly salary (excluding fringe benefits and bonuses) , Educ = the number of years of education, Exper = the number of months of experience, Train = the number of weeks of training, Gender = the gender of an individual; 1 for males, and 0 for females. Excel partial outputs corresponding to these models are available and shown below. Model A: Salary = β<sub>0</sub> + β<sub>1</sub>Educ + β<sub>2</sub>Exper + β<sub>3</sub>Train + β<sub>4</sub>Gender + ε   Model B: Salary = β<sub>0</sub> + β<sub>1</sub>Educ + β<sub>2</sub>Exper + β<sub>3</sub>Gender + ε   Assuming the same years of education and months of experience, what is the null hypothesis for testing whether the mean salary of males is greater than the mean salary of females using Model B? A)  H<sub>0</sub>: β<sub>3</sub> ≤ 0 B)  H<sub>0</sub>: β<sub>3</sub> ≥ 0 C)  H<sub>0</sub>: β<sub>3</sub>> 0 D)  H<sub>0</sub>: β<sub>3</sub> = 0 Model B: Salary = β0 + β1Educ + β2Exper + β3Gender + ε To examine the differences between salaries of male and female middle managers of a large bank, 90 individuals were randomly selected, and two models were created with the following variables considered: Salary = the monthly salary (excluding fringe benefits and bonuses) , Educ = the number of years of education, Exper = the number of months of experience, Train = the number of weeks of training, Gender = the gender of an individual; 1 for males, and 0 for females. Excel partial outputs corresponding to these models are available and shown below. Model A: Salary = β<sub>0</sub> + β<sub>1</sub>Educ + β<sub>2</sub>Exper + β<sub>3</sub>Train + β<sub>4</sub>Gender + ε   Model B: Salary = β<sub>0</sub> + β<sub>1</sub>Educ + β<sub>2</sub>Exper + β<sub>3</sub>Gender + ε   Assuming the same years of education and months of experience, what is the null hypothesis for testing whether the mean salary of males is greater than the mean salary of females using Model B? A)  H<sub>0</sub>: β<sub>3</sub> ≤ 0 B)  H<sub>0</sub>: β<sub>3</sub> ≥ 0 C)  H<sub>0</sub>: β<sub>3</sub>> 0 D)  H<sub>0</sub>: β<sub>3</sub> = 0 Assuming the same years of education and months of experience, what is the null hypothesis for testing whether the mean salary of males is greater than the mean salary of females using Model B?


Definitions:

Technology Budgets

Allocations of financial resources dedicated to the acquisition, maintenance, and upgrade of technological tools and infrastructure in educational settings.

Educational Delivery

The methods and processes through which educational content is provided to learners.

Homework Calendars

Tools used by educators and students to organize and plan out homework assignments over a period, usually a month, to manage time effectively.

Differentiate

To identify or ascertain differences between two or more entities or concepts.

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