<h3>
Answer: D) 141</h3>
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Explanation:
Let's consider a set of three values such that they're all equal to 35
{35,35,35}
This rather boring set has a mean of 35 and it's hopefully very clear why this is the case. The terms "mean" and "expected value" are interchangeable.
If we multiply everything by 4, then we get the new set {140,140,140}
Then add 1 to everything and we arrive at {141,141,141}. You can quickly see that the mean here is 141.
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You could play around with that original set of 3 values to make things more interesting. Let's say we subtract 1 from the first item and add 1 to the last item. So we could have {35,35,35} turn into {34,35,36}. You should find that the mean is still 35 here.
If we quadruple each item, then we have {34,35,36} turn into {136,140,144}
Finally, add 1 to everything to get {137,141,145}. Computing the mean of this set leads to 141.
These are just two examples you could do to help see why the answer is D) 141
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In a more general theoretical sense, we're saying the following
Y = mX+b
E[Y] = E[m*X+b]
E[Y] = E[m*X] + E[b]
E[Y] = m*E[X] + b
where Y is the transformed variable based on the random variable X. In this case, m = 4 and b = 1. Also, E[X] = 35.
So,
E[Y] = m*E[X] + b
E[Y] = 4*35 + 1
E[Y] = 141
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Why go through all this trouble? Well consider that you know a certain distribution is centered around 35. Then consider that you want to convert those measurements to some other unit. This conversion process is us going from variable X to variable Y. Think of it like a batch conversion of sorts.
A more real world example would be something like "we know the average temperature is 35 degrees Celsius. The question is: what is the average temperature in Fahrenheit?" The numbers would be different, but the idea still holds up.
