The scenario:Judge and Cable (2010) found a negative relationship between weight and income for women professionals. In our assignment, we will pretend we are replicating this study. To simply the weight variable, the women are classified into five categories that measure actual weight relative to height, from 1 = thinnest to 5 = heaviest. Income figures are annual income (in thousands) rounded to the nearest $1000.My question is based on my regression equation in the photo below. My question-Based on this information above, find another variable which is also an orthogonal variable, then state and explain what it will contribute to my regression equation. Please make sure you understand what this variable is as well. Please explain this in words, make it detailed as possible using proper terminology, and use full sentences. Thanks.My regression equation-

y = atb ( x) = y = -16. 41+ 103. 696 ( 1 ) =1 87. 286 1035 413 7 ( 3 - 1)