This is<span> not the exact, precise </span>definition<span> of a </span>limit. If you would like to see the more precise and mathematical definition<span> of a </span>limit<span> you should check out the The </span>Definition<span> of a </span>Limit<span> section at the end of this chapter. The </span>definition<span> given above </span>is<span> more of a “working” </span>definition<span>.</span>
The probability of picking one girl would be
. That is because there are 5 girls out of the 12 students, and the probability of an event occuring is:
.
Using that same logic, the next student should be easier. We reduced the student population by 1, so we have 11 possible ways it can happen now instead of 12, so that gives us:
, for the probability of picking a boy as the second pick.
And lastly, using the same logic shown above, the probability of picking a girl on the third pick would be:
.
We are not done, though. We have the separate probabilities, but now we have to multiply then together to figure out the probability of this exact event happening:

Which when reduced is:

X = 20
First, you move the 40 to the other side.
-2x=-40
Then, you divided -40 by -2.
x= -40/-2
x= 20
x is 20 because the negatives cancel out making it positive.
Answer:
Step-by-step explanation:
Hello!
You have two random samples obtained from two different normal populations.
Sample 1
n₁= 15
X[bar]₁= 350
S₁= 12
Sample 2
n₂= 17
X[bar]₂= 342
S₂= 15
At α: 0.05 you need to obtain the p-value for testing variances for a one tailed test.
If the statistic hypotheses are:
H₀: σ₁² ≥ σ₂²
H₁: σ₁² < σ₂²
The statistic to test the variances ratio is the Stenecor's-F test.
~

The p-value is:
P(
≤0.64)= 0.02
I hope it helps!