Suppose you are interested in investigating the wage gender gap using data on earnings of men and women. Which of the following models best serves this purpose? A. Wage=βo +β1, Female + u, where Female (=1 if female) is an indicator variable and u the omor term.
B. Wage =βo + u where u is the error term.
C. Female= βo+ β1 Wage + u where Female (=1 if female) is an indicator variable and u the error term.
D. Male =βo+β1 Female+ u where Male (=1 if male) is an indicator variable and u the error term
Consider the regression model
Wage=βo + β1Female + u
Where Fomale (=1 if female) is an indicator variable and u the error term.
Identify the dependent and independent variables in the regression model above.
Wage is the variable, while FP the varlabie.

A. Wage=βo +β1, Female + u, where Female (=1 if female) is an indicator variable and u the error term.

Wage = dependent variable

FP = Independent variable.

Step-by-step explanation:

The model selected model shows the relationship between the wages earned by male and female gender based on earnings of the two gender groups.

Wage is the dependent variable while factors upong which their wage depends on will be adopted as the independent variable. Since gender is categorical and cannot be used in that form during regression analysis. The it can be converted into a dummy or encoded variable. Such as treating female as = 1.

percentage - 25%

probability - 0.25

we know,

total amount of students in class = 20

total boys = 10

total girls = 10

no of girls who wear glasses = 10/2 = 5

probability of choosing a girl with glasses is =

number of girls wearing glasses/total number of students in the class = 5/20

thus, percentage of selecting a girl wearing glasses will be

= 5/20 × 100

= 5 × 5

25%

therefore,

probability will be 0.25

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