The law of gear reduction states that there’s always a decrease in the _______ of the output member, which is proportional to an
1 answer:
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<u>Given</u>:
Given that the radius of the cylinder is 6 m.
The height of the cylinder is 7 m.
We need to determine the surface area of the cylinder.
<u>Surface area of the cylinder:</u>
The surface area of the cylinder can be determined using the formula,
where r is the radius and h is the height of the cylinder.
Substituting r = 6 and h = 7 in the above formula, we get;
Simplifying, we get;
Multiplying, we get;
Thus, the surface area of the cylinder is 489.84 square meters.
Hence, Option a is the correct answer.
Answer:
There is a 91.15% probability that their mean life will be longer than 12 years.
Step-by-step explanation:
The Central Limit Theorem estabilishes that, for a random variable X, with mean and standard deviation
, a large sample size can be approximated to a normal distribution with mean
and standard deviation
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.
In this problem, we have that:
A manufacturer knows that their items have a normally distributed lifespan, with a mean of 13.2 years, and standard deviation of 3.1 years. This means that .
If you randomly purchase 12 items, what is the probability that their mean life will be longer than 12 years?
There are 12 items, so .
This is 1 subtracted by the pvalue of Z when .
By the Central Limit Theorem, we use the standard deviation of the sample in the Z score formula. That is:
has a pvalue of 0.0885
This means that there is a 1-0.0885 = 0.9115 = 91.15% probability that their mean life will be longer than 12 years.