Answer:
25
Step-by-step explanation:
So to solve for this, we need to set up proportional fractions, which I will help show you how to do.
First, if we are given an amount out of a total, we need to put it over x (if we are looking for the total). It looks like this:
12/x, 12 being the given number and x being the total.
If we are given the total but are looking for an amount, put the total at the bottom of the fraction (aka the denominator). It looks like this: x/16, 16 being the total amount and x being the amount out of the total.
We have a total of 40 test problems, so we can put our total at the bottom, x/40.
X is the amount of questions answered correctly (we are looking for x in the question).
We have answered 80% correct, so put 80% over 100 (100 being the total). It should look like this: 80/100.
Now we have our two fractions: x/40 & 80/100.
Set these up as an equation.
x/40 = 80/100.
Now this is where things may get tricky if you don't pay attention.
Multiply the numerator (the top number of a fraction) of x/40 by the denominator (the bottom number of a fraction) of 80/100.
Your product equation should look like this:
x times 100. This will give is 100x. Leave it at that.
Now, multiply the denominator of x/40 (the bottom number of the fraction) by the numerator (the top number of a fraction) of 80/100. It should look like this:
80 x 40. This will give us 3200.
Now set up our products as an equation.
100x = 3200.
To solve for x, divide both sides by 100.
3200/100 = 32.
x = 32.
I hope this helps and has taught you something!
Answer: 0
Step-by-step explanation: hope it helps
Answer: 0.10
Step-by-step explanation: The type 2 error is committed when the alternative hypothesis is rejected when it should have been accepted causing the researcher to accept the null hypothesis which is false.
Power is the probability of avoiding a type 2 error. That is ;
Power = 1 - P(type 2 error)
Given that power = 0.90 ; P(type 2 error) = probability of committing a type 2 error.
P(type 2 error)' = 1 - P(type 2 error) = Probability of not committing or avoiding a type 2 error
0.90 = 1 - P(type 2 error)
P(type 2 error) = 1 - 0.90
P(type 2 error) = 0.10
