We have been given an equation
. We are asked to solve the equation for t.
First of all, we will divide both sides of equation by a.


Now we will take natural log on both sides.

Using natural log property
, we will get:

We know that
, so we will get:


Now we will divide both sides by c as:


Therefore, our solution would be
.
Answer:
Te correct answer is c) 0.750
Step-by-step explanation:
Lets call:
A = {Allan wins the election}
B = {Barnes wins the election}
MA = {the model predicts that Allan wins}
MB = {the model predicts Barnes wins}
We know that the model has a 50:50 chance of correctly predicting the election winner when there are two candidates. Then:
P(MA | A) = 0.5 = P(MA | B)
P(MB | B) = 0.5 = P(MB | A)
The prior probability P(A) given by the election researcher is 0.75
We must find the posterior probability P(A | MB)
We use Bayes theorem:

We used the result:

Pretty sure the answer is 247,000
Answer:
B
Step-by-step explanation:
I just took the test
I would set up a proportion:

The proportion basically says, "if there are 5 kids meals for every 4 adult meals, that means 20 kids meals would mean x adult meals." Just cross multiply and then solve for x:

That means there are 20 kids meals sold and 16 adult meals sold, so the result is:
36 meals in total.