Line l has a slope of 2. The line through which of the following pair of points is perpendicular to l?
2 answers:
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Answer:
a)
b) Wind capacity will pass 600 gigawatts during the year 2018
Step-by-step explanation:
The world wind energy generating capacity can be modeled by the following function
In which W(t) is the wind energy generating capacity in t years after 2014, W(0) is the capacity in 2014 and r is the growth rate, as a decimal.
371 gigawatts by the end of 2014 and has been increasing at a continuous rate of approximately 16.8%.
This means that
(a) Give a formula for W , in gigawatts, as a function of time, t , in years since the end of 2014 . W= gigawatts
(b) When is wind capacity predicted to pass 600 gigawatts? Wind capacity will pass 600 gigawatts during the year?
This is t years after the end of 2014, in which t found when W(t) = 600. So
We have that:
So we apply log to both sides of the equality
It will happen 3.1 years after the end of 2014, so during the year of 2018.
Answer:
78.88% probability that the mean thickness in the sample of 100 points is within 0.1 mm of the target value
Step-by-step explanation:
To solve this question, we need to understand the normal probability distribution and the central limit theorem.
Normal probability distribution
Problems of normally distributed samples are 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.
Central Limit Theorem
The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean and standard deviation
, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean
and standard deviation
.
For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.
In this problem, we have that:
What is the probability that the mean thickness in the sample of 100 points is within 0.1 mm of the target value?
This is the pvalue of Z when X = 2 + 0.1 = 2.1 subtracted by the pvalue of Z when X = 2 - 0.1 = 1.9. So
X = 2.1
By the Central Limit Theorem
has a pvalue of 0.8944
X = 1.9
has a pvalue of 0.1056
0.8944 - 0.1056 = 0.7888
78.88% probability that the mean thickness in the sample of 100 points is within 0.1 mm of the target value