ple: Mass production process • Estimated 6% defective rate. • Randomly sample 50 units each week. •The r.v. X = # defectives in 50 units (a) What is the distribution of X? Binomial (n = 50, p = 0.06) (b) What is the probability of 3 defectives P[X =3] =b(3;50,0.06) 50 (39) (0.06) α Page (0.06)³ (1-0.06) 50-3

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Example: Mass production process
• Estimated 6% defective rate.
Randomly sample 50 units each week.
• The r.v. X = # defectives in 50 units
(a) What is the distribution of X?
Binomial (n = 50, p = 0.06)
(b) What is the probability of 3 defectives?
P[X=3]=b(3:50,0.06)
50
- ($9) (0.06)
3
(0.06)³ (1-0.06) 50-3
Transcribed Image Text:Example: Mass production process • Estimated 6% defective rate. Randomly sample 50 units each week. • The r.v. X = # defectives in 50 units (a) What is the distribution of X? Binomial (n = 50, p = 0.06) (b) What is the probability of 3 defectives? P[X=3]=b(3:50,0.06) 50 - ($9) (0.06) 3 (0.06)³ (1-0.06) 50-3
Mass production process (cont' d)
X=# defectives in 50 units~ Bin(n = 50, p = 0.06)
(c) What is the probability of more than 3?
P[X >3] =1-P[X ≤ 3]=1- B(3;50,0.06)
=1-b(1:50,0.06)
t=0
- 2 (50)
(59) (0.06)
1=0
=1-
(0.06)' (1-0.06)50-
Transcribed Image Text:Mass production process (cont' d) X=# defectives in 50 units~ Bin(n = 50, p = 0.06) (c) What is the probability of more than 3? P[X >3] =1-P[X ≤ 3]=1- B(3;50,0.06) =1-b(1:50,0.06) t=0 - 2 (50) (59) (0.06) 1=0 =1- (0.06)' (1-0.06)50-
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