1.3 yrs = ? hrs ...?
2 answers:
You might be interested in
Given that and
, we can say the following:
Now, remember what happens if we have a negative square root: it becomes an imaginary number. We don't want this, so we want to make sure whatever is under a square root is greater than 0 (given we are talking about real numbers only).
Thus, let's set what is under both square roots to be greater than 0:
Since both of the square roots are in the same function, we want to take the union of the domains of the individual square roots to find the domain of the overall function.
Now, let's look back at the function entirely, which is:
Since is on the bottom of the fraction, we must say that
, since the denominator can't equal 0. Thus, we must exclude
from the domain.
Thus, our answer is Choice C, or .
<em>If you are wondering why the choices begin with the symbol, it is because this is a way of representing that
lies within a particular set.</em>
Answer:
a) P(X < 99) = 0.2033.
b) P(98 < X < 100) = 0.4525
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 normal distributions can be solved using the z-score formula.
In a set with mean and standard deviation
, the z-score 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 p-value, 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.
Mean of 100 and variance of 36.
This means that
Sample of 25:
This means that
(a) P(X<99)
This is the pvalue of Z when X = 99. So
By the Central Limit Theorem
has a pvalue of 0.2033. So
P(X < 99) = 0.2033.
b) P(98 < X < 100)
This is the pvalue of Z when X = 100 subtracted by the pvalue of Z when X = 98. So
X = 100
has a pvalue of 0.5
X = 98
has a pvalue of 0.0475
0.5 - 0.0475 = 0.4525
So
P(98 < X < 100) = 0.4525