Suppose a shipment of 400 components contains 68 defective and 332 non-defective computer components. From the shipment you take
1 answer:
Answer:
mean (μ) = 4.25
Step-by-step explanation:
Let p = probability of a defective computer components =
let q = probability of a non-defective computer components =
Given random sample n = 25
we will find mean value in binomial distribution
The mean of binomial distribution = np
here 'n' is sample size and 'p' is defective components
mean (μ) = 25 X 0.17 = 4.25
<u>Conclusion</u>:-
mean (μ) = 4.25
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Answer: 2185
Step-by-step explanation:
Let p be the proportion of visitors are campers.
Given : The Tennessee Tourism Institute (TTI) plans to sample information center visitors entering the state to learn the fraction of visitors who plan to camp in the state.
The prior proportion of visitors are campers : p=0.35
Allowable error : E= 2%= 0.02
We know that the z-value for 95% confidence =
Then by Central Limit Theorem , the required sample size would be :
Simply , we get
[Rounded to the next whole number.]
Hence, the smallest sample size to estimate the population proportion of campers =2185
Answer:
20
85%
Step-by-step explanation:
You are given the function
If n is the number of hours, then initially n=0 and
If S(n) is the function of exponential growth, then it can be represented as
where I is the initial amount, r -is the percent growth rate and n is the number of hours.
If b = 1.85, we can represent it as b = 1 + 0.85. Thus, the hourly percent growth rate of the bacteria would be 0.85=85%.