Transforming Data Into Information ESSAY

Transforming Data Into Information

The Woodmill Company makes windows and door trim products. The first step in the process is to rip dimension (2 × 8,2 × 10, etc.) lumber into narrower pieces. Currently, the company uses a manual process in which an experienced operator quickly looks at a board and determines what rip widths to use. The decision is based on the knots and defects in the wood. A company in Oregon has developed an optical scanner that can be used to determine the rip widths. The scanner is programmed to recognize defects and to determine rip widths that will optimize the value of the board. A test run of 100 boards was put through the scanner and the rip widths were identified. However, the boards were not actually ripped. A lumber grader determined the resulting values for each of the 100 boards, assuming that the rips determined by the scanner had been made. Next, the same 100 boards were manually ripped using the normal process. The grader then determined the value for each board after the manual rip process was completed. The resulting data, in the file, Woodmill Data.xls , consists of manual rip values and scanner rip values for each of the 100 boards.

Instructions
You are a process manager at the Woodmill Company tasked with determining if an optical scanner would be beneficial. Write a 4–5 page report to your supervisor (including a cover page and a Source List page) in which you:

Summarize the Woodmill Company’s problem of ripping dimension lumber into narrower pieces.
Develop a frequency distribution for the board values for the scanner and the manual process.
Generate appropriate descriptive statistics for both manual and scanner values.
Analyze the frequency distribution and descriptive statistics for both manual and scanner processes. Use Excel to create your charts.
Determine which process generates more values that were more than 2 standard deviations from the mean (manual or scanner).
Evaluate which process has less relative variability, using frequency distribution and descriptive statistics.
Recommend whether the optical scanner is the best option for the company.

Woodmill Data

Board	Scanner	Manual
ID	Value	Value
1	16.23	7.07
2	31.07	14.02
3	18.44	21.33
4	18.32	24.78
5	33.11	18.48
6	47.65	32.34
7	16.11	6.85
8	31.28	24.48
9	21.18	18.35
10	35.1	19.8
11	28.41	24.11
12	35.92	28.3
13	19.34	11.83
14	20.9	11.17
15	35.63	35.92
16	25.51	13.69
17	24.85	13.74
18	21.87	20.83
19	22.12	24.62
20	31.96	13.26
21	39.88	12.85
22	27.94	21.08
23	34.11	34.63
24	41.45	16.77
25	31.68	10.91
26	43.14	41.37
27	42.6	26.73
28	40.07	22.15
29	19.86	36.94
30	37.03	39.44
31	20.42	38.45
32	28.7	19
33	22.53	35.4
34	41.99	14.88
35	27.35	14.81
36	34.95	8.7
37	28.57	34.43
38	27.66	27.58
39	30.89	22.24
40	34.87	27.16
41	35.2	12.41
42	34.33	15.17
43	25.01	23.6
44	37.06	23.64
45	28.09	27.27
46	26.43	30.71
47	43.47	11.27
48	34.76	35.69
49	21.36	20.97
50	22.62	21.28
51	36.58	29.11
52	43.78	25.37
53	33.27	25.88
54	33.68	46.22
55	35.94	20.06
56	34.76	16.72
57	40.1	27.29
58	28.99	28.29
59	30.57	28.3
60	30.4	33.49
61	28.44	26.5
62	34.02	30.13
63	30.83	30.3
64	27.18	25.85
65	47.87	14.48
66	32.7	24.96
67	38.64	22.14
68	25.83	21.22
69	31.78	20.92
70	19.65	24.05
71	36.98	13.14
72	32.27	19.02
73	25.57	28.68
74	23.93	23.57
75	12.67	37.28
76	25.59	25.17
77	34.41	26.21
78	26.81	17.16
79	19.12	30.01
80	32.04	33.25
81	23.84	8.16
82	26.45	27.98
83	25.41	38.52
84	29.6	21.14
85	22.7	16.56
86	28.67	7.61
87	18.37	13.17
88	29.35	23.92
89	33.71	21.14
90	35.91	20.11
91	23.66	30.37
92	23.39	20.05
93	34.02	13.52
94	30.47	15.69
95	38.81	17.56
96	34.71	23.98
97	26.35	23.94
98	32.58	8.74
99	24.71	21.62
100	27.76	24.67

Transforming Data Into Information ESSAY

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