Before answering our question on equal pay why i

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before answering our question on equal pay? Why? If Null is rejected, what is the variable's coefficient value?
4 Between the lecture results and your results, what is your answer to the question of equal pay for equal work for males and females? Why?
With the results of the compa-regression equation and the t-test on average compa-ratios 5 What does regression analysis show us about analyzing complex measures?
either showing where the data you used is located Be sure to copy the appropriate data columns from the data tab to the right for your use this week. ? (Do not include compa-ratio in this question.) What is the data input ranged used for this question: U,V,W,X,Y, Z ull. T = 2.0106347576 0.2787105932 ant are midpoint, Age, and Service. non significant correlations you thought would be? e significant since the group numbers varied. . sed in Q1 along with ndings by answering the following questions. or Q1. ssible variables except compa-ratio? AA, AB 0.05 F-stat and ANOVA gnificance 2.27883561674987E-34
Reject the null hypothesis The p-value is less than (<) 0.05. f the variable coefficients. (Write a single The variable coefficient is not significant The variable coefficient is significant 0.05 T Stat and t-test For Coefficients Reject the null hypothesis if p-value < 0.05. egression output above. you reject the null, place the coefficient in the table. Perf. Rat. Seniority Raise Gender -1.81525480847156 -0.36497481 0.92623067 3.3673509969 0.076629592356861 0.716961692 0.35961806 0.0016335374 Not Not Not Reject 3.0865361246 e equation? nder gs being equal? The input variables are significantly related to compa-ratio outcomes.
ults, what else would you like to know
s I see that it's very evident that females are getting more pay than males. There is a viloation of the E Regression analysis shows us the relationship between a dependent variable and atleast one independ
Use Cell K08 for the Excel test outcome location. Salary Midpoint Age Performance Rating Salary 1 Midpoint 0.987421 1 Age 0.554381 0.567110663644 1 Performance Rating 0.149715 0.1917507685954 0.13923840742 1 Service 0.461791 0.4711467003565 0.56513320943 0.22570075937644 Raise -0.048472 -0.0289134051608 -0.1804268525 0.67365976296224 Use Cell M34 for the Excel test outcome location. SUMMARY OUTPUT Regression Statistics Multiple R 0.99081286925 R Square 0.98171014188 Adjusted R Square 0.97866183219 Standard Error 2.8051100168 Observations 50
ANOVA df SS Regression 7 17738.7098273341 Residual 42 330.482972665914 Total 49 18069.1928 Coefficients Standard Error pair, we will use it for each variable separatelyIntercept -3.8212776752 4.0841592430757 Midpoint 1.21278041636 0.03244949603513 Age 0.05443469855 0.07226751414194 Performance Rating -0.09301312 0.05123970450884 Service -0.033341523 0.09135294367813 Raise 0.64387763041 0.69515904423762 Gender 3.08653612465 0.91660659297305 Degree -0.030017385 0.80516017939531 Degree -0.03728126 0.97043739 Not
Equal Pay Act because females are getting more pay than man for equal work. dent variable. Through this analysis we can see how a dependent value can change when independent v
Salary 65.6 26.9 33.2 61.4 50.2 73.1 Service Raise 41.6 23.7 75.1 23.2 23.7 1 58.7 0.10278690028543 1 42.1 25 22.2 50.8 68.8 34.2 24.4 35 72.7 54.2 24.8 54.7 25.1 23.9 40.5 77.4 73 49.8 24 26.6
MS F Significance F 2534.10140390487 322.0507 2.27883562E-34 7.86864220633129 t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% -0.9356338594365 0.354811 -12.063444715 4.420889365 -12.063444715 4.4208893646956 37.3743991291981 7.31E-34 1.147294682144 1.278266151 1.14729468214 1.2782661505725 0.75323884045265 0.455508 -0.09140704944 0.200276447 -0.0914070494 0.2002764465527 -1.8152548084716 0.07663 -0.19641903012 0.01039279 -0.1964190301 0.0103927901328 -0.3649748065955 0.716962 -0.21769922709 0.151016181 -0.2176992271 0.1510161811846 0.92623067447544 0.359618 -0.75901011731 2.046765378 -0.7590101173 2.0467653781366 3.36735099693988 0.001634 1.236749130688 4.936323119 1.23674913069 4.9363231186111 -0.0372812587491 0.970437 -1.65489641086 1.594861641 -1.6548964109 1.5948616408932
variable are put into the analysis.
Midpoint Age Service Raise Gender Degree 57 34 85 8 5.7 0 0 31 52 80 7 3.9 0 0 31 30 75 5 3.6 1 1 57 42 100 16 5.5 0 1 48 36 90 16 5.7 0 1 67 36 70 12 4.5 0 1 40 32 100 8 5.7 1 1 23 32 90 9 5.8 1 1 67 49 100 10 4 0 1 23 30 80 7 4.7 1 1 23 41 100 19

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