Noah and Maggie are making a rectangular picture frame.They want the length of the frame to be three inches longer than the widt
1 answer:
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Answer:
Jerry does cases per hour (Rounded to 2 decimal places). As we cannot do 0.11 cases. We can say Jerry does 2 cases per hour.
Step-by-step explanation:
to find the number of cases per hour, we have to divide the number of cases by number of hours taken for those cases,
Number of cases per hour =
= cases per hour
= cases per hour
= cases per hour
= cases per hour (Rounded to 2 decimal places)
As we cannot do 0.11 cases. We can say Jerry does 2 cases per hour.
Answer:
64.56% probability that between 17 and 25 circuits in the sample are defective.
Step-by-step explanation:
Binomial probability distribution
Probability of exactly x sucesses on n repeated trials, with p probability.
Can be approximated to a normal distribution, using the expected value and the standard deviation.
The expected value of the binomial distribution is:
The standard deviation of the binomial distribution is:
Normal probability distribution
Problems of normally distributed samples can be solved using the z-score formula.
In a set with mean and standard deviation
, the zscore of a measure X is given by:
The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.
When we are approximating a binomial distribution to a normal one, we have that ,
.
In this problem, we have that:
So
Probability that between 17 and 25 circuits in the sample are defective.
This is the pvalue of Z when X = 25 subtrated by the pvalue of Z when X = 17. So
X = 25
has a pvalue of 0.7626.
X = 17
has a pvalue of 0.1170.
0.7626 - 0.1170 = 0.6456
64.56% probability that between 17 and 25 circuits in the sample are defective.