At first, we will find the probability of "Y" to become "1" or "-1" . Namely, we have:
"P(Y=1)=P(\\{X =2k|k\\in {\\mathbb{N}}\\})=\\sum_{k=1}^{+\\infty}P(X=2k)=\\sum_{k=1}^{+\\infty}\\frac{1}{2^{2k}}=\\sum_{k=1}^{+\\infty}\\frac{1}{4^{k}}."
Using the formula for an infinite geometric series, we have:
"P(Y=1)=\\sum_{k=1}^{+\\infty}\\frac{1}{4^{k}}=\\frac14\\frac{1}{1-\\frac14}=\\frac13" .
In the same way we obtain:
"P(Y=-1)=P(\\{X =2k-1|k\\in {\\mathbb{N}}\\})=\\sum_{k=1}^{+\\infty}P(X=2k-1)=\\newline\\sum_{k=1}^{+\\infty}\\frac{1}{2^{2k-1}}=2\\sum_{k=1}^{+\\infty}\\frac{1}{4^{k}}=\\frac23."
We remind that the expected value for discrete random variable Y is(see e.g., https://en.wikipedia.org/wiki/Expected_value):
"E[Y]=P(Y=1)*1+P(Y=-1)*(-1)=\\frac13-\\frac23=-\\frac13"
Answer:"-\\frac13"
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