Both inequality is different positive and negative and it would be
Part (a)
P(A) = 0.5
P(B) = 0.4
P(B/A) = 0.6
P(A and B) = P(A)*P(B/A)
P(A and B) = 0.5*0.6
P(A and B) = 0.3
<h3>Answer: 0.3</h3>
==========================================
Part (b)
We'll use the result from part (a)
P(A or B) = P(A) + P(B) - P(A and B)
P(A or B) = 0.5 + 0.4 - 0.3
P(A or B) = 0.6
<h3>Answer: 0.6</h3>
===========================================
Part (c)
A and B are not independent since P(B) does not equal P(B/A). The fact that event A happens changes the probability P(B). Recall that P(B/A) means "probability P(B) based on event A already happened". A and B are independent if P(B) = P(B/A).
Events A and B are not mutually exclusive since P(A or B) is not zero.
<h3>Answer: Neither</h3>
Answer:


Step-by-step explanation:
We know that the mean and the standard error of the sampling distribution of the sample proportions will be :-


, where p=population proportion and n= sample size.
Given : The proportion of students at a college who have GPA higher than 3.5 is 19%.
i.e. p= 19%=0.19
The for sample size n= 25
The mean and the standard error of the sampling distribution of the sample proportions will be :-


Hence , the mean and the standard error of the sampling distribution of the sample proportions :


Answer:
The probability that he chooses a yellow ball is 5/14. If he removes all the orange balls, the probability that he will choose a red ball is 2/10.
Step-by-step explanation:
Simple logic.
1.09÷3= .3633 each
4.49÷12= .37416 each
8.78÷24= .3658 each
so the first one