Suppose that you would like to study the relationship between weight (in lbs) and the following characteristics: marital status (variable married takes value 1 if married and spouse is present in the household, 2 if I if married but the spouse is not present in the household, 3 Widowed, 4 Divorced, 5 Separated, 6 never married), education (in years), age (in years), sex (variable female takes values 1 if female and otherwise), a region of living (variable region takes values 1 if northeast, 2 if Midwest,3 if south, 4 if west), and race (variable takes values 1 if white, if 2 black, 3 if Hispanic, 4 if other). Below is the table with the estimates. 1. How many regressions did I estimate? II. Write the estimated regression as an equation for column (3)? III. Interpret all coefficients in column (4)? IV. Is the effect of being married without a spouse in the household on weight statistically different than 0? V. Is the effect of living in the west on weight statistically different than 5? -6.71 0.45 Table 1. Estimated regression of characteristics on weight (2) Variable weight weight weight weight Cocff/Std. en. Coeff./Std. err Coeff/Std. em. Coeff./Std.err. Married: Married, sps not in hh -8319 -894 -8.60 -7.16 (3.50) (3.50) (3.50) (3.50) Widowed -4.19 -10.07 -10.06 -10.85 (2.52) (2.56) (2.56) (2.54) Divorced -5.61*** -6.79 -7.82*** (1.12) (1.12) (1.12) (1.12) Separated -5.52 -5.51 -5.36 -7.80* (2.20) (2.20) (2.20) (2.20) Never Married -0.59 2.45 2.60 1.57 (1.11) (1.13) (1.13) (1.13) Age (in years) 0.46 0.46 (0.04) (0.04) (0.04) Education of Individual -0.36 -0.33 -0.31 in years) (0.15) (0.15) (0.15) Region Midwest (1.14) (1.13) South 3.490 2.56 (1.09) (1.08) West 1.27 3.68" (1.19) (1.20) Race Black 10.800 (1.25) Hispanic -5.57" (1.51) Other -20.77 (1.97) Constant 171.63 157.61*** 154.37 194.86*** (0.48) (2.66) (2.80) (2.86) R-squared 0.00 0.01 0.01 0.02 RSS 47147538.8 46786786.8 46732384.5 46175808 2 IN, of cases 17870.00 17870.00 17870.00 17870.00 p