It depends really. If you stay close to the present, then predicting future results isn't too bad. The further you go out, the more unpredictable things get. This is because the points may deviate from the line of best fit (aka regression line) as time wears on. Of course, it also depends on what kind of data we're working with. Some pairs of variables are naturally going to correlate very strongly together. An example would be temperature versus ice cream sales.
The probability of E and F expressed as P(E and F) equals;0.12
<h3>How to solve Conditional Probability?</h3>
We are given;
P(E) = 0.2
P(F|E) = 0.6
Now, P(F/E) is known as conditional probability and it means the probability of event F given the probability of another event E. This can be expressed as; P(F|E) = P(E and F)/P(E)
Thus;
P(E and F) = 0.2 * 0.6
P(E and F) = 0.12
Read more about Conditional Probability at; brainly.com/question/23382435
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By definition, the volume of a rectangular prism is given by:
V1 = (w) * (l) * (h)
Where,
w: width
l: long
h: height
Substituting we have:
60 = (w) * (l) * (h)
if the length and the width double, and the height remains the same, we have:
V2 = (2w) * (2l) * (h)
Rewriting:
V2 = 4 * ((w) * (l) * (h))
V2 = 4 * V1
Substituting we have:
V2 = 4 * (60)
V2 = 240 cubic feet
Answer:
the new volume will be:
V2 = 240 cubic feet
