Answer:
It's easy.
Step-by-step explanation:
The square root of something is just the reverse of some squared.
For example, if you do 3 to the power of 2 (3^2) you get 9. now if you reverse that you would do square root. would be 3. Think of it like multiplication and division. If you do 10*5 you get 50. All you have to do is reverse it after that 50/5 = 10. See.
The only difference it square(2) root and squared(2) are only with the number 2. Meaning you can't do 3 to the power of 3 (3^3) and expect to square root it to get the reverse. For example, 3 to the power of 3 (3^3) is 27. But the square root of 27 is NOT 3, it is 5.2
You get it?
Answer:
8.31 weeks
Step-by-step explanation:
Given that the cost of one share of Apple stock, C=$120
Rate is the increment of the stock value, R= 5%/week=0.05 / week.
Assuming that after t week, the stock has been sold for $180.
Since the stock value increased at 5% every week, so, the interest is compounded weekly, so
[taking log both sides]
weeks
Hence, after 8.31 weeks the stock has been sold for $180.
Answer:
0.039 = 3.9% probability that the random sample of 16 people in the elevator will exceed the weight limit
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.
If n variables are added, the mean is and the standard deviation is
In this problem:
What is the probability that the random sample of 16 people in the elevator will exceed the weight limit?
This is 1 subtracted by the pvalue of Z when X = 2750. So
By the Central Limit Theorem
has a pvalue of 0.961
1 - 0.961 = 0.039
0.039 = 3.9% probability that the random sample of 16 people in the elevator will exceed the weight limit