Question

Suppose that a local chapter of sales professionals in the greater San Francisco area con- ducted a survey of its membership to study the relationship, if any, between the years of experience and salary for individuals employed in inside and outside sales positions. On the survey, respondents were asked to specify one of three levels of years of experience: low (1–10 years), medium (11–20 years), and high (21 or more years). A portion of the data obtained follows. The complete data set, consisting of 120 observations, is contained in the file named “SalesSalary”.

Develop a 95% confidence interval estimate of the mean annual salary for all salespersons, regardless of years of experience and type of position.Use descriptive statistics to summarize the data.

Develop a 95% confidence interval estimate of the mean salary for inside salespersons.

Develop a 95% confidence interval estimate of the mean salary for outside salespersons.

Use analysis of variance to test for any significant differences in Salary due to position. Use a 0.05 level of significance, and for now, ignore the effect of years of experience.

USING EXCEL NOT MINITAB!!! It won't let me post the excel file so let me know how to send that.

HW #2	Salary ($)	Position	Experience
1	53938	Inside	Medium
2	52694	Inside	Medium
3	70515	Outside	Low
4	52031	Inside	Medium
5	62283	Outside	Low
6	57718	Inside	Low
7	79081	Outside	High
8	48621	Inside	Low
9	72835	Outside	High
10	54768	Inside	Medium
11	52282	Inside	Medium
12	55632	Inside	Low
13	63856	Outside	Low
14	51827	Inside	Medium
15	51948	Inside	Low
16	56588	Inside	Medium
17	68858	Outside	Low
18	63478	Outside	Low
19	83846	Outside	Medium
20	59253	Inside	High
21	53464	Inside	Low
22	83176	Outside	Medium
23	60949	Inside	High
24	52833	Inside	Low
25	72914	Outside	High
26	83040	Outside	Medium
27	64288	Outside	Low
28	64562	Inside	High
29	52644	Inside	High
30	55959	Inside	Low
31	88730	Outside	Medium
32	77683	Outside	Medium
33	56339	Inside	High
34	71345	Outside	Low
35	63799	Inside	Low
36	78074	Outside	High
37	65546	Outside	Low
38	59057	Inside	Medium
39	66024	Outside	Low
40	59457	Inside	High
41	79383	Outside	Medium
42	61128	Outside	Low
43	54122	Inside	Low
44	78710	Outside	High
45	58814	Inside	Low
46	59276	Inside	Low
47	75869	Outside	Medium
48	57549	Inside	Medium
49	76762	Outside	Medium
50	60993	Outside	Low
51	63362	Inside	Medium
52	53231	Inside	High
53	62115	Inside	High
54	56080	Inside	Medium
55	53392	Inside	Medium
56	61299	Outside	Low
57	53894	Inside	High
58	82794	Outside	Medium
59	56990	Inside	Low
60	77403	Outside	High
61	78936	Outside	High
62	54282	Inside	Medium
63	78850	Outside	Medium
64	54592	Inside	High
65	56461	Inside	Low
66	74389	Outside	High
67	49422	Inside	Low
68	86692	Outside	Medium
69	77356	Outside	High
70	58055	Inside	Medium
71	77820	Outside	High
72	77801	Outside	High
73	58053	Inside	Medium
74	78169	Outside	Medium
75	68560	Outside	Low
76	66320	Outside	High
77	67237	Outside	Low
78	62225	Outside	Low
79	58866	Inside	High
80	77311	Outside	High
81	76863	Outside	High
82	81750	Outside	Medium
83	58749	Inside	High
84	52638	Inside	Medium
85	62675	Inside	Medium
86	51027	Inside	High
87	62881	Outside	Low
88	75791	Outside	High
89	61680	Outside	Low
90	59768	Inside	High
91	56568	Inside	High
92	82622	Outside	Medium
93	75326	Outside	High
94	57719	Inside	High
95	57366	Inside	High
96	57670	Inside	Low
97	52072	Inside	Low
98	68569	Outside	High
99	81526	Outside	Medium
100	82059	Outside	Medium
101	74374	Outside	High
102	51119	Inside	Low
103	80696	Outside	Medium
104	56352	Inside	Low
105	77622	Outside	High
106	69142	Outside	Low
107	67603	Outside	High
108	60561	Outside	Low
109	51246	Inside	Medium
110	54891	Inside	Low
111	87090	Outside	Medium
112	55482	Inside	High
113	53464	Inside	Low
114	58568	Inside	Medium
115	58080	Inside	High
116	78702	Outside	Medium
117	83131	Outside	Medium
118	57788	Inside	High
119	53070	Inside	Medium
120	60259	Outside	Low

Answer 1

Mean=	64925.48
Std.dev=	10838.67

Anova: Single Factor
SUMMARY
Groups	Count	Sum	Average	Variance
High	40	2653547	66338.68	94080544
Low	40	2392785	59819.63	36060691
Medium	40	2744725	68618.13	1.86E+08
ANOVA
Source of Variation	SS	df	MS	F	P-value	F crit
Treatments	1668100099	2	8.34E+08	7.926144	0.000591	3.073763
Error	12311642893	117	1.05E+08
Total	13979742992	119

As, F>F(critical), we can infer that there is significant differences in salary due to various experiences.