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 df SS MS F Regression 4 28,045,960.12 7,011,490.03 43.23 Residual 85 13,787,729.88 162,208.59 Total 89 41,833,690.00 Coefficients Standard Error t-stat p-value Intercept 4,663.31 365.37 12.76 1.85E-21 Educ 140.66 20.15 6.98 6.07E-10 Exper 3.36 0.47 7.17 2.54E-10 Train 1.17 3.72 0.31 0.7543 Gender 615.15 97.33 0.32 1.16E-08 Model B: Salary = β0 + β1Educ + β2Exper + β3Gender + ε df SS MS F Regression 3 28,029,969.88 9,343,323.29 58.21 Residual 86 13,803,720.12 162,508.37 Total 89 41,833,690.00 Coefficients Standard Error t-stat p-value Intercept 4,713.26 327.1967 14.40 1.21E-24 Educ 139.54 19.7253 7.07 3.78E-10 Exper 3.35 0.4649 7.20 2.10E-10 Gender 609.25 94.9920 6.41 7.39E-09 A group of female managers considers a discrimination lawsuit if on average their salaries can be statistically proven to be lower by more than $500 than the salaries of their male peers with the same level of education and experience. Using Model B, what is the alternative hypothesis for testing the lawsuit condition? HA:β3>500 HA:β3 ≠ 500 HA:β3≤500 HA:β3<500