Ok so you would start by getting rid of the fraction. You should know the steps for that by now but here this is what it would look like
3y/4+10=2y/4 Simplify
3y/4+10=1y/210=-1y I really simplified the last part but this is what it looks like:
- 
= -1y
10=-1yy=-10
By their increase or decrease
<span>Exactly 33/532, or about 6.2%
This is a conditional probability, So what we're looking for is the probability of 2 gumballs being selected both being red. So let's pick the first gumball.
There is a total of 50+150+100+100 = 400 gumballs in the machine. Of them, 100 of the gumballs are red. So there's a 100/400 = 1/4 probability of the 1st gumball selected being red.
Now there's only 399 gumballs in the machine and the probability of selecting another red one is 99/399 = 33/133.
So the combined probability of both of the 1st 2 gumballs being red is
1/4 * 33/133 = 33/532, or about 0.062030075 = 6.2%</span>
Answer:
Abdullah is correct.
Step-by-step explanation:
The bottle contained originally 12 fl oz, so 12 fl oz is 100%.
The box now contains 20% more, so now it contains 120% of 12 fl oz.
120% * 12 fl oz = 1.2 * 12 fl oz = 14.4 fl oz
Also, 20% is 1/5. Abdullah divided 12 oz into 5 equal parts, and then he added one more 1/5. He interpreted the problem correctly. The amount in the new bottle is the amount of the old bottle plus 20% of that old amount.
Kanna considers the original amount to be 80%. When he adds another 20%, he is adding 1/4 of 12 which is too much. That is why he gets an incorrect answer that is to high. He interpreted the problem incorrectly. For him, the old bottle has 20% less than the new bottle. That is incorrect.
Abdullah is correct.
Answer:
b. type II
Step-by-step explanation:
given that food inspectors inspect samples of food products to see if they are safe. This can be thought of as a hypothesis test with the following hypotheses.
H0: the food is safe
Ha: the food is not safe
It was concluded from the hypothesis test that the food is safe while it was not actually safe.
This is a case of false acceptance of null hypothesis when it is false.
In hypothesis test, there are two errors. a type I error is the rejection of a true null hypothesis while a type II error is the non-rejection of a false null hypothesis
So this is type II error because we did not reject a false null hypothesis.
