Probability & Statistics Ch.2 Section 1 Question 1

· Mohammad-Ali Bandzar

Solutions for “Probability and Statistics: The Science of Uncertainty” (Second Edition). These are solutions I have come up with; I offer no guarantee of accuracy.

Question

Let S={1,2,3...}S=\{1,2,3...\} and let X(s)=s2X(s)=s^2 and Y(s)=1sY(s)=\frac{1}{s} for sSs\in S. For each of the following quantities, determine (with explanation) whether or not it exists. If it does exist, then give its value.

a) minsSX(s)\min_{s\in S}X(s)

b) maxsSX(s)\max_{s\in S}X(s)

c) minsSY(s)\min_{s\in S}Y(s)

d) maxsSY(s)\max_{s\in S}Y(s)

Solution

(a) minsSX(s)\min_{s\in S}X(s)

Since s2s^2 is strictly increasing as ss \rightarrow \infty, we know that X(1)X(1) will be our minimum value. Therefore:

minsSX(s)=12=1\min_{s\in S}X(s)=1^2=1

(b) maxsSX(s)\max_{s\in S}X(s)

Since s2s^2 is strictly increasing without bound as ss \rightarrow \infty and since our sample space goes to positive infinity, we can conclude that X(s)X(s) is an unbounded random variable (similar to Example 2.1.10 from the textbook). Therefore:

maxsSX(s)=DNE (Does Not Exist)\max_{s\in S}X(s) = \text{DNE (Does Not Exist)}

(c) minsSY(s)\min_{s\in S}Y(s)

Does not exist. Since our sample space SS goes from 11\rightarrow\infty, we should look at the function f(x)=1xf(x)=\frac{1}{x} where xWx\in \mathbb{W}. Since our function is strictly decreasing on this domain, naturally the largest number in our sample space SS would produce our minimum value. Since we cannot plug s=s=\infty into Y(s)Y(s), we know that there is no minimum.

In other words: since limxf(x)=0\lim_{x\rightarrow\infty}f(x)=0, our minimum value should be zero, but since there is no sSs\in S such that Y(s)=0Y(s)=0, the minimum does not exist.

(d) maxsSY(s)\max_{s\in S}Y(s)

Since our function is strictly decreasing on its domain (the sample space), we know that Y(s)=maxsSY(s)Y(s)=\max_{s\in S}Y(s) when ss is the lowest possible number. In this case, that means s=1s=1. Therefore:

maxsSY(s)=Y(1)=1\max_{s\in S}Y(s)=Y(1)=1