Answer:
0.589
Step-by-step explanation:
THis is a conditional probability question. Let's look at the formula first:
P (A | B) = P(A∩B)/P(B)
" | " means "given that".
So, it means, the <u><em>"Probabilty A given that B is equal to Probability A intersection B divided by probability of B."</em></u>
<u><em /></u>
So we want to know P (Female | Undergraduate ). This in formula is:
P (Female | Undergraduate) = P (Female ∩ Undergraduate)/P(Undergraduate)
Now,
P (Female ∩ Undergraduate) means what is common in both female and undergraduate? There are 43% female that are undergrads. Hence,
P (Female ∩ Undergraduate) = 0.43
Also,
P (Undergraduate) is how many undergrads are there? There are 73% undergrads, so that is P (undergraduate) = 0.73
<em>plugging into the formula we get:</em>
P (Female | Undergraduate) = P (Female ∩ Undergraduate)/P(Undergraduate)
=0.43/0.73 = 0.589
this is the answer.
Answer:
138 students
Step-by-step explanation:
207/9 = 23
23*6=138
Answer:
Step-by-step explanation:
Hello!
The variable of interest is:
X: number of daily text messages a high school girl sends.
This variable has a population standard deviation of 20 text messages.
A sample of 50 high school girls is taken.
The is no information about the variable distribution, but since the sample is large enough, n ≥ 30, you can apply the Central Limit Theorem and approximate the distribution of the sample mean to normal:
X[bar]≈N(μ;δ²/n)
This way you can use an approximation of the standard normal to calculate the asked probabilities of the sample mean of daily text messages of high school girls:
Z=(X[bar]-μ)/(δ/√n)≈ N(0;1)
a.
P(X[bar]<95) = P(Z<(95-100)/(20/√50))= P(Z<-1.77)= 0.03836
b.
P(95≤X[bar]≤105)= P(X[bar]≤105)-P(X[bar]≤95)
P(Z≤(105-100)/(20/√50))-P(Z≤(95-100)/(20/√50))= P(Z≤1.77)-P(Z≤-1.77)= 0.96164-0.03836= 0.92328
I hope you have a SUPER day!
Part A: Shiloh would collect data on which student spends the most time at the beach
Part B: It is a statistical question
