Set Events:
T=tests positive~T=tests negativeP=subject is pregnant~P=subject is not pregnant
We are givenP(T n ~P)=0.02P(~T n P)=0.03P(P)=0.7
recall by definition of conditional probabilityP(A|B)=P(A n B)/P(B)
Need to find P(P|~T)
First step: make a contingency diagram of probabilities (intersection, n)
P ~P sum
T 0.67 0.02 0.69=P(T)
~T 0.03 0.28 0.31=P(~T)
sum 0.70 0.30 1.00
=P(P) =P(~P)
therefore
P(P|~T)=P(P n ~T)/P(~T)=0.03/0.31 [ both read off the contingency table ]
=0.0968
A simple way to look at how to check for equivalent fractions<span> is to do what is called “cross-multiply”, which means multiple the numerator </span>of<span> one </span>fraction <span>by the denominator </span>of<span> the </span>other fraction<span>. Then do the same thing in reverse. Now compare the two answers to see </span>if<span> they are </span>equal<span>.</span>
Answer:
5 to 2
Step-by-step explanation:
You can simplify both 20 and 8 by 4.
20/4 = 5
8/4 = 2
Choice D : look at where you think the line would be if it followed the direction of the data so that about half of the points fell above the line and half below. The two most important things to note are the slope of the line and y intercept.
This is a negative relationship as the line falls as you read it from left to right. That eliminates choice C. Next, it appears the line of best fit would have a y intercept around 10 on the y axis and then fall down and to the right cutting the data. Note that choices A and B have y intercepts that don't make sense for the data. Choice D does have a y intercept of 10 and a negative slope.
Answer:
This means 100000 possible zip codes if repeatable
Step-by-step explanation: