Module F - Attributes Sampling
MODULE F
Attributes Sampling
LEARNING OBJECTIVES
Review
Checkpoints
Exercises, Problems,
and Simulations
1.
Identify the objectives of attributes sampling,
define deviation conditions, and define the
population for an attributes sampling
application.
1, 2, 3, 4
51, 53, 54, 55, 71 (partial),
73 (parts a – b), 74 (parts a –
b), 75 (part a), 76 (partial),
77 (partial), 79
2.
Understand how various factors influence the
size of an attributes sample.
5, 6, 7
52 (partial), 71 (partial), 72
(parts a – b), 75 (parts b –
c), 76 (partial), 77 (partial),
78, 79
3.
Determine the sample size for an attributes
sampling application.
8, 9
52 (partial), 60, 61, 62,
63, 64, 71 (partial), 72
(part c), 74 (part c), 75
(parts d – e), 80 (partial)
4.
Identify various methods of selecting an
attributes sample.
10, 11, 12
56 (partial), 57, 58, 59, 71
(partial), 73 (parts c-d), 74
(part d)
5.
Evaluate the results of an attributes sampling
application by determining the upper limit rate
of deviation (ULRD).
13, 14, 15, 16,
17, 18, 19, 20,
21, 22
52 (partial), 56 (partial),
65, 66, 67, 68, 69, 70, 71
(partial), 72 (parts d – f),
73 (part d), 74 (parts e –
g), 75 (parts f – h), 77
(parts g-h), 80 (partial)
6.
Define sequential sampling and discovery
sampling and identify when these types of
sampling applications would be used.
23, 24
7.
Understand how to apply nonstatistical
sampling to attributes testing.
24, 25
74
MODF-1