Answer:
Probability of stopping the machine when [tex] X < 9 [/tex] is 0.0002
Probability of stopping the machine when [tex] X < 10 [/tex] is 0.0013
Probability of stopping the machine when [tex] X < 11 [/tex] is 0.0082
Probability of stopping the machine when [tex] X < 12 [/tex] is 0.0399
Step-by-step explanation:
There is a random binomial variable [tex] X [/tex] that represents the number of units come off the line within product specifications in a review of [tex] n [/tex] Bernoulli-type trials with probability of success [tex] 0.91 [/tex]. Therefore, the model is [tex] {15 \choose x} (0.91) ^ {x} (0.09) ^ {(15-x)} [/tex]. So:
[tex] P (X < 9) = 1 - P (X \geq 9) = 1 - [{15 \choose 9} (0.91)^{9}(0.09)^{6}+...+{ 15 \choose 15}(0.91)^{15}(0.09)^{0}] = 0.0002 [/tex]
[tex] P (X < 10) = 1 - P (X \geq 10) = 1 - [{15 \choose 10}(0.91)^{10}(0.09)^{5}+...+{15 \choose 15} (0.91)^{15}(0.09)^{0}] = 0.0013 [/tex]
[tex] P (X < 11) = 1 - P (X \geq 11) = 1 - [{15 \choose 11}(0.91)^{11}(0.09)^{4}+...+{15 \choose 15} (0.91)^{15}(0.09)^{0}] = 0.0082[/tex]
[tex] P (X < 12) = 1- P (X \geq 12) = 1 - [{15 \choose 12}(0.91)^{12}(0.09)^{3}+...+{15 \choose 15} (0.91)^{15}(0.09)^{0}] = 0.0399 [/tex]
Probability of stopping the machine when [tex] X < 9 [/tex] is 0.0002
Probability of stopping the machine when [tex] X < 10 [/tex] is 0.0013
Probability of stopping the machine when [tex] X < 11 [/tex] is 0.0082
Probability of stopping the machine when [tex] X < 12 [/tex] is 0.0399