Statistical discrimination requires that a person be evaluated and paid Multiple Choice at the low end of a normal distribution of a group. on her own merits only. at the mean of a normal distribution of a group. at the high end of a normal distribution of a group.
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Statistical discrimination refers to a situation where individuals are treated not based on their individual characteristics but based on the average characteristics of the group they belong to. This type of discrimination occurs when decision-makers use group Show more…
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Suppose that salary data distribution of employees in a company resembles normal. Hence the requirement for the Empirical rule is met. The average salary and standard deviation are 75,000 dollars and 5,000 dollars, respectively. Four employees: A, B, C and D are paid $95,000, $65,000, $55,000 and $85,000, respectively. Which statement is correct? Select one: a. The salary of employee C can be considered as an outlier b. The salary of employee B can be considered as an outlier c. The salary of employee D can be considered as an outlier d. The salary of employee A is quite normal for the company
Shubham S.
Suppose that a worker’s wage (w) depends not only on his/her own test score (T), but also on the average test score ( ) of workers in his/her racial group, i.e., w equals alpha T space plus space left parenthesis 1 minus alpha right parenthesis top enclose T If the parameter alpha is equal to zero, then the applicant’s wage depends ____________ . a. entirely on chance. b. on both the average test score of the group and his/her own test score, but the average test score of the group is a more important determinant of his/her wage. c. on both the average test score of the group and his/her own test score, but his/her own test score is a more important determinant of his/her wage. d. entirely on the average test score of the group. e. entirely on his/her own test score.
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An investigator hired by a client suing for sex discrimination has developed a multiple regression model for employee salaries for the company in question. In this multiple regression model, the salaries are in thousands of dollars. For example, a data entry of 35 for the dependent variable indicates a salary of $35,000. The indicator (dummy) variable for gender is coded as X1 = 0 if male and X1 = 1 if female. The computer output of this multiple regression model shows that the coefficient for this variable (X1) is -4.2. The t test showed that X1 was significant at a = .1. This result implies that for male and female workers of the company, on the average, females earn $4,200 less than males. on the average, males earn $4,200 less than females. on the average, salaries do not differ between males and females. on the average, males have 4.2 more years of experience than females. on the average, females have 4.2 more years of experience than males.
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