Expectation of Normal Distribution

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SUMMARY

The discussion centers on calculating the expected values E[Y], E[Z], E[YZ], E[Y^2], and E[Z^2] for the function Y = a + bZ + cZ², where Z is a standard normal random variable. Participants highlight the need for integration by parts to compute E[Z³] and E[Z⁴], given that E[Z] = 0 and E[Z²] = 1. The moment-generating function (MGF) of the normal distribution is also introduced as an alternative method for finding higher moments, specifically M(t) = exp(μt + σ²t²/2).

PREREQUISITES
  • Understanding of standard normal distribution and its properties
  • Familiarity with integration by parts
  • Knowledge of moment-generating functions
  • Basic calculus skills for evaluating integrals
NEXT STEPS
  • Learn how to apply integration by parts in probability theory
  • Study the moment-generating function for various distributions
  • Explore the derivation of expected values for higher moments of the normal distribution
  • Review the cumulative distribution function (CDF) of the normal distribution
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Students and professionals in statistics, data science, and mathematics who are working with probability distributions and need to compute expected values for functions of random variables.

MattFox
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Let Y = a + bZ + cZ2 where Z (0,1) is a standard normal random variable.
(i) Compute E[Y], E[Z], E[YZ], E[Y^2] and E[Z^2].
HINT: You will need to determine E[Z^r], r = 1, 2, 3, 4. When r = 1, 2 you should
use known results. Integration by parts will help when r = 3, 4.
I am struggling with the part of the question involving E[Z^3] and E[Z^4]. Clearly E[Z]=0 and E[Z^2]=1 but I do not no where to proceed when computing higher powers of Z. Any help would be greatly appreciated.

Thanks
 
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Expected value of a function g of z is E[g(z)] = \int_{-\infty}^{+\infty}g(z)f(z)dz where f is the pdf of z.
 
So am I right in thinking I let g(z) = z^3 and f(z)= 1/(sigma * sqrt2pi) ... and then use integration by parts?
 
That should be it.
 
I'm not really getting anywhere with the integration by parts. Is there any hint you could offer or show me a step I could be missing out?
 
Can you post what you have so far?
 
Ok so,

INT u dv = uv - INT v du

Then i let u = Z^3 and dv = the pdf of the normal dist.

Im lost when it comes to integrating the pdf and I'm not sure how it will condense down to a manageable solution. Sorry about the lack of symbols, I'm not sure how to properly upload images yet.
 

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If dv = the pdf of the normal dist., then what is v?

(If dv = f(z) and v = F(z), what is F?)
 
F(z) is the cdf of the normal distribution.

So E(Z^3) = Z^3 * F(Z) - INT 3Z^2 * F(Z).

Do i then need to apply integration by parts again? I'm sorry if I'm asking too many questions I just really don't understand what I'm trying to achieve as a solution.
 
  • #10
Or more accurately, what form the solution will take i.e an integer, function of Z...
 
  • #11
u = Z^3 and dv = f(z)dz ===> v = F(z)

E(Z^3) = INT u dv = [uv] - INT v du = [Z^3 * F(Z)] - INT F(Z) 3Z^2 dZ, where each of the [uv] expression and the last INT are evaluated over (-infinity, +infinity).

E.g., [uv] = u(+infinity)v(+infinity) - u(-infinity)v(-infinity) ... but (infinity)^3 is not a real number, so something's amiss. See http://en.wikipedia.org/wiki/Integration_by_parts
 

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