please see the table in comment

b) What would the point prediction be for the temporary female worker who studied until high school at the age of 28, according to the model? a) 203,527 b) 148,482 c) 157,856 d) 138,749 e) 189,635 C) What would the point prediction be for a 46-year-old who studied after high school, according to the model? a) 187,167 b) 227,742 0) 210,542 d) 125,489 e) 68,568 d) What would be the point prediction for a 37-year-old, temporary male worker who did not attend primary school according to the model? a) 95,325 b) 92,462 c) 81,425 d) 87,963 e) 109,090 In the regression model established in the study conducted on 114 employees in India, the variables are defined as follows: UG : Weekly wage income (rupee), Age : age (year), DE2 : artificial variable that takes value 1 for workers who have studied until primary school, DE3 = High School Dummy variable that takes value 1 for workers with up to 1 education, DE4 = dummy variable that takes value 1 for educated workers after high school, DSG = dummy variable that takes 1 for permanent workers, 0 for temporary workers, Dcins : 1 for male workers, 1 for female workers Reference category 0 is temporary male workers who have not studied primary school. Here, it is explored how age, gender, education level and permanent job affect weekly wage. For this purpose, the following regression model will be estimated: in 06'.- = 1?, + 321/45,- + 33052 + 34053 + 3505., + 33056 + 3703-33 + 0,- a) 131 =? O 3,622 0 65,216 0 6,828 O 2,124 0 12,736 Bz=? 014549 O 0029 0 3,933 0 7,012 0 5,739 33 :7 02345 0 5,443 024,018 O 1,658 00,158 4 =? 0 61,579 0 2,785 0 12,857 0 0,505 O 0978 35 =3 0 5,735 0 0,624 0 1,895 0 0,112 O 1506 E, =? 0 31,216 0 0,012 O 4758 0 0,781 0 0319 F7 :2 O 2,3?8 0 83,262 0 0,786 0 1,123 0 0,666