Bernoulli Variance: Calculating Var[Xi] as a Function of p

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Homework Help Overview

The discussion revolves around understanding how the variance of a Bernoulli random variable, Var[Xi], depends on the probability of success, p. Participants are exploring the expression of variance as a function of p, specifically in the form of σ²(p).

Discussion Character

  • Conceptual clarification, Mathematical reasoning

Approaches and Questions Raised

  • Participants discuss the calculation of variance for a Bernoulli random variable and question the interpretation of expressing it as a function σ²(p). There is uncertainty about whether this involves calculating variance itself or simply recognizing its dependence on p.

Discussion Status

Some participants have provided clarifications regarding the meaning of p and the notation used for variance. There is an acknowledgment of the relationship between variance and probability, but no consensus has been reached on the interpretation of the question.

Contextual Notes

Participants are navigating the definitions and implications of variance in the context of Bernoulli trials, with some expressing confusion about the phrasing of the problem statement.

Gekko
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Homework Statement



Show how Var(Xi) depends on p writing it as a function [tex]\sigma[/tex]^2(p)

The Attempt at a Solution



Var[Xi] = E[Xi^2] - E^2[Xi] = p-p^2 = p(1-p)

not sure where to go from here to get it in the form [tex]\sigma^2[/tex](p) ?
 
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Please clarify you question. In particular, what is "p"? The mean?

If I understand the rest, The standard deviation, [itex]\sigma[/itex] is defined as the square root of the variance. The variance is [itex]\sigma^2[/itex].
 
p in this case is the probability of success. Xi is a Bernoulli random variable.

This is a standard Bernoulli question but I just don't understand what the question is asking when it says "writing it as a function sigma^2(p)". Does that mean calculate the variance of the probability? Surely not. In which case it must just be p(1-p)?
 
think about common function notation: when you write a function of [tex]x[/tex] you use [tex]f(x)[/tex]. Since the variance in the binomial setting is a function of [tex]p[/tex], the corresponding way to write it is [tex]\sigma^2(p)[/tex] - variance as a function of [tex]p[/tex]. It looks awkward, but you're stuck with it.
 
I see. That makes sense. Thanks
 

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