SITE X

Respondent#	Age Category	Income	#Desserts Out per Month	# Meals out per Month
1000	22-25	5000	4	5
1001	30-35	100000	5	15
1002	26-30	75000	3	24
1003	18-21	40000	1	16
1004	30-35	100000	12	4
1005	26-30	50000	9	19
1006	30-35	20000	1	8
1007	30-35	100000	18	12
1008	30-35	20000	14	7
1009	30-35	100000	5	20
1010	30-35	75000	1	0
1011	18-21	30000	0	6
1012	22-25	30000	4	12
1013	18-21	30000	0	3
1014	18-21	5000	1	5
1015	over 35	50000	1	8
1016	30-35	40000	1	2
1017	26-30	20000	11	3
1018	30-35	100000	11	13
1019	18-21	30000	0	3
1020	30-35	30000	3	13
1021	26-30	75000	1	21
1022	18-21	5000	1	10
1023	22-25	20000	1	2
1024	18-21	10000	0	0
1025	22-25	5000	13	20
1026	26-30	75000	5	11
1027	over 35	20000	4	2
1028	22-25	5000	14	6
1029	over 35	100000	12	13
1030	18-21	10000	0	3
1031	18-21	10000	1	7
1032	26-30	100000	12	7
1033	22-25	10000	3	5
1034	22-25	50000	13	9
1035	22-25	20000	6	3
1036	26-30	20000	6	11
1037	18-21	10000	0	2
1038	30-35	75000	1	4
1039	22-25	30000	20	10
1040	30-35	100000	2	7
1041	18-21	5000	0	4
1042	22-25	10000	8	1
1043	22-25	20000	21	2
1044	30-35	20000	9	3
1045	18-21	20000	0	19
1046	18-21	5000	1	3
1047	26-30	5000	10	3
1048	22-25	5000	15	5
1049	22-25	50000	15	14
1050	22-25	40000	21	23
1051	22-25	50000	13	10
1052	22-25	5000	4	4
1053	18-21	40000	1	10
1054	30-35	100000	3	16
1055	26-30	50000	20	13
1056	18-21	30000	0	2
1057	18-21	30000	0	7
1058	30-35	100000	7	17
1059	26-30	30000	6	11
1060	18-21	10000	0	1
1061	26-30	75000	18	1
1062	over 35	100000	8	11
1063	30-35	5000	1	3
1064	18-21	30000	1	10
1065	22-25	100000	7	12
1066	30-35	5000	2	2
1067	over 35	50000	7	8
1068	26-30	20000	2	2
1069	26-30	50000	7	3
1070	26-30	30000	3	8
1071	18-21	20000	0	3
1072	30-35	40000	10	18
1073	26-30	30000	3	4
1074	18-21	5000	0	12
1075	over 35	10000	21	2
1076	26-30	20000	25	2
1077	18-21	5000	0	1
1078	22-25	50000	5	9
1079	over 35	20000	2	7
1080	18-21	30000	0	9
1081	30-35	100000	14	15
1082	26-30	5000	2	3
1083	30-35	100000	9	16
1084	26-30	20000	18	3
1085	18-21	40000	0	1
1086	18-21	30000	1	3
1087	18-21	30000	0	6
1088	26-30	5000	18	1
1089	over 35	10000	8	4
1090	22-25	75000	13	6
1091	18-21	10000	1	4
1092	26-30	20000	11	3
1093	26-30	40000	23	15
1094	18-21	10000	1	5
1095	22-25	75000	17	2
1096	18-21	30000	0	3
1097	22-25	75000	12	5
1098	22-25	100000	17	21
1099	18-21	5000	1	9
1100	18-21	40000	1	9
1101	over 35	100000	8	2
1102	22-25	5000	4	1
1103	26-30	10000	5	1
1104	26-30	75000	5	8
1105	26-30	30000	5	3
1106	over 35	100000	0	1

Site Y

Respondent#	Age Category	Income	#Desserts Out per Month	# Meals out per Month
2000	30-35	75000	0	13
2001	30-35	30000	10	7
2002	26-30	5000	4	24
2003	18-21	20000	0	5
2004	30-35	100000	5	16
2005	26-30	20000	10	19
2006	30-35	75000	8	9
2007	30-35	100000	10	5
2008	30-35	30000	5	9
2009	30-35	75000	4	13
2010	30-35	100000	4	4
2011	18-21	30000	7	5
2012	22-25	5000	9	14
2013	18-21	30000	0	3
2014	18-21	30000	0	13
2015	over 35	100000	0	17
2016	30-35	100000	7	3
2017	26-30	50000	4	5
2018	30-35	100000	17	14
2019	18-21	20000	10	8
2020	30-35	75000	13	9
2021	26-30	10000	2	23
2022	18-21	5000	11	8
2023	30-35	40000	0	7
2024	30-35	30000	15	10
2025	22-25	50000	2	16
2026	over 35	10000	4	2
2027	over 35	40000	12	3
2028	22-25	30000	14	15
2029	over 35	40000	10	12
2030	18-21	10000	0	0
2031	18-21	10000	8	13
2032	26-30	40000	0	6
2033	22-25	30000	16	22
2034	22-25	30000	3	27
2035	22-25	20000	6	6
2036	26-30	5000	7	20
2037	18-21	20000	19	7
2038	30-35	5000	8	14
2039	22-25	5000	5	6
2040	30-35	40000	1	14
2041	18-21	40000	8	19
2042	over 35	10000	6	3
2043	22-25	100000	2	28
2044	over 35	50000	24	9
2045	18-21	10000	5	7
2046	18-21	10000	18	13
2047	26-30	5000	2	17
2048	22-25	10000	2	5
2049	22-25	100000	3	17
2050	22-25	30000	4	14
2051	22-25	30000	11	25
2052	22-25	20000	1	9
2053	18-21	30000	18	19
2054	over 35	20000	19	4
2055	26-30	30000	12	9
2056	18-21	10000	5	17
2057	18-21	40000	11	5
2058	30-35	100000	1	4
2059	26-30	20000	1	11
2060	18-21	20000	14	5
2061	26-30	40000	3	3
2062	over 35	50000	2	3
2063	30-35	30000	10	4
2064	18-21	10000	9	1
2065	22-25	75000	9	9
2066	30-35	100000	8	4
2067	over 35	100000	15	11
2068	over 35	20000	1	2
2069	over 35	50000	2	10
2070	26-30	100000	2	25
2071	18-21	20000	23	13
2072	30-35	75000	18	1
2073	26-30	10000	3	8
2074	18-21	5000	17	21
2075	over 35	10000	2	3
2076	26-30	30000	8	4
2077	18-21	5000	20	12
2078	22-25	5000	0	6
2079	over 35	100000	7	15
2080	18-21	40000	14	23
2081	30-35	40000	0	12
2082	26-30	30000	18	9
2083	30-35	100000	3	15
2084	30-35	30000	17	19
2085	18-21	5000	8	6
2086	18-21	20000	1	9
2087	18-21	30000	3	21
2088	26-30	100000	2	24
2089	over 35	100000	15	6
2090	22-25	20000	4	17
2091	18-21	30000	1	13
2092	26-30	100000	12	13
2093	26-30	20000	1	9
2094	18-21	10000	6	9
2095	22-25	5000	17	18
2096	18-21	10000	0	22
2097	22-25	20000	4	13
2098	22-25	100000	0	5
2099	18-21	10000	6	7
2100	18-21	10000	11	3
2101	over 35	40000	15	2
2102	22-25	75000	2	6
2103	30-35	30000	5	14
2104	26-30	5000	2	11
2105	30-35	100000	1	4
2106	over 35	10000	10	7

Please help, having a hard time understanding this practice problem assignment, please explain how you got the answer. Need this for studying.

Level 2 - Analyzing Demographic Data for La Rosa Restaurant You have recently decided to test your entrepreneurial skills by opening a restaurant that you plan to name La Rosa. In your restaurant, you plan to feature specialty desserts, along with fine cuisine. One critical decision you must make is where to locate the restaurant. Right now, you are considering two different locations- one near a large retail area on the fringe of several affluent suburbs (site X), and the other in the downtown district (site Y). Before making the decision, you have hired a local market research firm to provide you with some demographics of the areas and the specific dining habits of the local population