We have:
Event A ⇒ P(A) = 0.16
Event B ⇒ P(B) = 0.09
Probability of event B given event A happening, P(B|A) = P(A∩B) / P(A) = 0.12
By the conditional probability, the probability of event A and event B happens together is given by:
P(B|A) = P(A∩B) ÷ P(A)
P(B|A) = P(A∩B) ÷ 0.16
0.12 = P(A∩B) ÷ 0.16
P(A∩B) = 0.12 × 0.16
P(A∩B) = 0.0192
When two events are independent, P(A) × P(B) = P(A∩B) so if P(A∩B) = 0.0192, then P(B) will be 0.0192 ÷ 0.16 = 0.12 (which take us back to P(B|A))
Since P(B|A) does not equal to P(B), event A and event B are not independent.
Answer: <span>Events A and B are not independent because P(B|A) ≠ P(B)</span>
Answer:
In my opinion this is the whole w
Step-by-step explanation:
Basically, every zero a number has to the end, the higher the scientific notation will be. Because 1000 has three zeroes, 10^5 will go to 10^8. So, you will travel 7.5 x 10^8 miles.
Answer:
So the answer for this case would be n=22547 rounded up to the nearest integer
Step-by-step explanation:
Let's define some notation
represent the sample mean
population mean (variable of interest)
represent the population standard deviation
n represent the sample size
represent the margin of error desire
The margin of error is given by this formula:
(a)
And on this case we have that ME =+1 and we are interested in order to find the value of n, if we solve n from equation (a) we got:
(b)
The critical value for 99% of confidence interval now can be founded using the normal distribution. The significance would be 
and the critical value 
, replacing into formula (b) we got:
So the answer for this case would be n=22547 rounded up to the nearest integer
