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suppose x is a random variable with mean 5 and variance 2. then, e[3x - 3] is 12 and var[3x - 3] is 18 .

User Dyslexit
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Final answer:

The new expected value after the linear transformation 3x - 3 is 12 and the new variance is 18 for a random variable x with mean 5 and variance 2.

Step-by-step explanation:

According to the information provided, we are given a random variable x with a mean of 5 and a variance of 2.


When transforming this random variable using the linear transformation 3x - 3, we need to find the new expected value (E[3x - 3]) and the new variance (Var[3x - 3]).

The expected value of a linear transformation of a random variable is calculated by E[aX + b] = aE[X] + b, where a and b are constants. In this case, a = 3 and b = -3.

So, the new expected value is E[3x - 3] = 3E[x] - 3 = 3(5) - 3 = 15 - 3 = 12.

Regarding the variance, it is affected only by the scaling factor a, not by the shift b. Importantly, Var[aX + b] = a2Var[X].

Hence, the new variance is Var[3x - 3] = 32Var[x] = 9(2) = 18.

User Huupke
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