Let P_m be the population proportion of all males who spent at least $1,500, and let p_f be the similar proportion for females. A 90% confidence interval for the difference p_m minus p_f has which of the following limits? (Because of potential roundoff, choose the closest.)

Click here to reference the data needed to answer the question.

a. 0.170 to 0.470

b. 0.116 to 0.524

c. -0.470 to -0.170

d. 0.142 to 0.499

Person Gender Married Age Children Salary Spent Male Yes 45 2 77000 1540 Male Yes 43 1 85300 2220 W I Male Yes 42 N 88400 1040 Male Yes 40 2 100300 790 Male Yes 47 1 105000 2780 Female No 36 0 6460 740 Female Yes 65 4 122700 720 Female Yes 38 2 50400 530 9 Male Yes 54 5 86700 1020 10 Male Yes 45 1 114500 1660 11 Male No 31 1 102600 430 12 Female No 50 3 62000 680 13 Male Yes 44 110800 2230 14 Female No 43 61200 670 15 Female Yes 54 3 128000 510 16 Female Yes 44 81500 2020 17 Female Yes 45 730 INNH 74900 18 Male 57 95700 2910 19 Male Yes 50 1 123400 2340 20 Female No 49 1 60600 1830 21 Female No 50 2 98700 620 22 Male Yes 34 3 7610 670 23 Female No 45 1 89800 660 24 Male No 56 1 82900 2120 25 Male Yes 46 2 98500 1570 26 Female No 33 1 77000 380 w 1180 27 Male Yes 47 93900 28 Yes 38 31200 2020 Male 29 Male Yes 54 146200 1050 30 Male No 40 1 89400 850 31 Male Yes 60 1 129700 2690 32 Male Yes 0 105200 2620 33 Male No 28 1 60000 390 34 Female No 51 0 95200 1950 35 Male No 32 0 82000 1390 36 Female No 51 2 9530 770 37 Female Yes 97500 610 w w 38 Female No 42 67600 400 39 Female Yes 46 2 68900 1080 40 Male Yes 48 3 126300 360 41 Male Yes 3 120900 4300 42 Female Yes 39 3 64600 510 43 Female Yes 59 3 91900 1140 44 Male No 32 1 50000 1530 45 Female Yes 59 2 77500 2210 46 Male No 27 0 72800 420 47 Female Yes 34 1 57200 1230 48 Female Yes 48 48900 1230 NW 19 Male Yes 52 120700 1400 50 Male Yes 56 1 104900 3080 51 Female Yes 86900 710 52 Female No 7550 1010 53 Male Yes 45 104000 1660 INNE 54 Female Yes 49600 1390 55 Male Yes 36 72500 820 56 Male les 43 0 124500 2930 Female Yes 58 4 77100 1010 W Male les 47 71900 1760 Male No 47 1 103100 1220 60 Male No 38 1 77900 550 61 Male No 0 86400 1990 62 Male No 44 0 130300 2950 63 Female Yes 44 3 68800 520 64 Male No 34 1 93500 1270 Male Yes 47 2 105700 2200 56 Female No 50 0 7550 18 80 67 Male Yes 53 3 130900 1000 68 Male No 34 75900 1110 59 Male Yes 45 0 88400 3160 70 Male Yes 45 UT 59900 1210 71 Male No 41 2 65700 1420 72 Male Yes 47 109800 2130 73 Male No 53 0 144400 2060 74 Female No 0 70700 2490 75 Male No 1 115100 1850 76 Female No 64 2 131600 1040 77 Female Yes 29 6 78500 110 78 Male Yes 63200 2520 45 79 Female Yes 4 96400 930 80 Female Yes 2 77300 1790 81 Male No 1 89100 630 82 Female No 59 7380 2030 83 Male Yes 57 1 109700 1800 84 Male Yes 58 2 115600 1910 35 Male No 57 1 97600 1900 86 Male Yes 42 3 7880 1200 87 Male No 39 92300 900 88 Female Yes 46 67100 1240 39 Female No 41 80500 820 90 Female Yes 52 72600 1010 31 Male Yes 1 94100 3030 92 Male No 0 135900 1200 93 Female Yes 41 78700 1260 94 Female Yes 48 2 102700 770 95 Female No 51 3 119500 160 96 840 Male No 34 1 74300 97 1910 Male No 44 0 103900 98 Female No 45 87200 560 Female Yes 52 61400 1590 100 Male No 90700 1460Person Gender Married Age Children Salary Spent Male Yes 45 2 77000 1540 Male Yes 43 1 85300 2220 W I Male Yes 42 N 88400 1040 Male Yes 40 2 100300 790 Male Yes 47 1 105000 2780 Female No 36 0 6460 740 Female Yes 65 4 122700 720 Female Yes 38 2 50400 530 9 Male Yes 54 5 86700 1020 10 Male Yes 45 1 114500 1660 11 Male No 31 1 102600 430 12 Female No 50 3 62000 680 13 Male Yes 44 110800 2230 14 Female No 43 61200 670 15 Female Yes 54 3 128000 510 16 Female Yes 44 81500 2020 17 Female Yes 45 730 INNH 74900 18 Male 57 95700 2910 19 Male Yes 50 1 123400 2340 20 Female No 49 1 60600 1830 21 Female No 50 2 98700 620 22 Male Yes 34 3 7610 670 23 Female No 45 1 89800 660 24 Male No 56 1 82900 2120 25 Male Yes 46 2 98500 1570 26 Female No 33 1 77000 380 w 1180 27 Male Yes 47 93900 28 Yes 38 31200 2020 Male 29 Male Yes 54 146200 1050 30 Male No 40 1 89400 850 31 Male Yes 60 1 129700 2690 32 Male Yes 0 105200 2620 33 Male No 28 1 60000 390 34 Female No 51 0 95200 1950 35 Male No 32 0 82000 1390 36 Female No 51 2 9530 770 37 Female Yes 97500 610 w w 38 Female No 42 67600 400 39 Female Yes 46 2 68900 1080 40 Male Yes 48 3 126300 360 41 Male Yes 3 120900 4300 42 Female Yes 39 3 64600 510 43 Female Yes 59 3 91900 1140 44 Male No 32 1 50000 1530 45 Female Yes 59 2 77500 2210 46 Male No 27 0 72800 420 47 Female Yes 34 1 57200 1230 48 Female Yes 48 48900 1230 NW 19 Male Yes 52 120700 1400 50 Male Yes 56 1 104900 3080 51 Female Yes 86900 710 52 Female No 7550 1010 53 Male Yes 45 104000 1660 INNE 54 Female Yes 49600 1390 55 Male Yes 36 72500 820 56 Male les 43 0 124500 2930 Female Yes 58 4 77100 1010 W Male les 47 71900 1760 Male No 47 1 103100 1220 60 Male No 38 1 77900 550 61 Male No 0 86400 1990 62 Male No 44 0 130300 2950 63 Female Yes 44 3 68800 520 64 Male No 34 1 93500 1270 Male Yes 47 2 105700 2200 56 Female No 50 0 7550 18 80 67 Male Yes 53 3 130900 1000 68 Male No 34 75900 1110 59 Male Yes 45 0 88400 3160 70 Male Yes 45 UT 59900 1210 71 Male No 41 2 65700 1420 72 Male Yes 47 109800 2130 73 Male No 53 0 144400 2060 74 Female No 0 70700 2490 75 Male No 1 115100 1850 76 Female No 64 2 131600 1040 77 Female Yes 29 6 78500 110 78 Male Yes 63200 2520 45 79 Female Yes 4 96400 930 80 Female Yes 2 77300 1790 81 Male No 1 89100 630 82 Female No 59 7380 2030 83 Male Yes 57 1 109700 1800 84 Male Yes 58 2 115600 1910 35 Male No 57 1 97600 1900 86 Male Yes 42 3 7880 1200 87 Male No 39 92300 900 88 Female Yes 46 67100 1240 39 Female No 41 80500 820 90 Female Yes 52 72600 1010 31 Male Yes 1 94100 3030 92 Male No 0 135900 1200 93 Female Yes 41 78700 1260 94 Female Yes 48 2 102700 770 95 Female No 51 3 119500 160 96 840 Male No 34 1 74300 97 1910 Male No 44 0 103900 98 Female No 45 87200 560 Female Yes 52 61400 1590 100 Male No 90700 1460