The variance of h(X) is the expected value of the squared difference between h(X) and its expected value. V[h(X)] = 0ncx? =E {n(x) – Elh(x)]}² · p(x) D. Use this definition to find V(ax + b). [Hint: With h(X) = ax + b, E[h(X)] = aµ + b where u = E(X).] (ax + b - E[ax + b])² · p(x) = L( - Elax)"p«) E[ax] - ([ - (L L(x - E(X))²p(x) II II
The variance of h(X) is the expected value of the squared difference between h(X) and its expected value. V[h(X)] = 0ncx? =E {n(x) – Elh(x)]}² · p(x) D. Use this definition to find V(ax + b). [Hint: With h(X) = ax + b, E[h(X)] = aµ + b where u = E(X).] (ax + b - E[ax + b])² · p(x) = L( - Elax)"p«) E[ax] - ([ - (L L(x - E(X))²p(x) II II
Algebra & Trigonometry with Analytic Geometry
13th Edition
ISBN:9781133382119
Author:Swokowski
Publisher:Swokowski
Chapter5: Inverse, Exponential, And Logarithmic Functions
Section: Chapter Questions
Problem 9T
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![The variance of h(X) is the expected value of the squared difference between h(X) and its expected value.
V[h(X)] = 0ncx? =E {n(x) – Elh(x)]}² · p(x)
D.
Use this definition to find V(ax + b). [Hint: With h(X) = ax + b, E[h(X)] = aµ + b where u = E(X).]
(ax + b - E[ax + b])² · p(x) = L(
- Elax)"p«)
E[ax]
- ([
- (L
L(x - E(X))²p(x)
II
II](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fc32f563a-6b55-4123-a4c3-1254c39a7403%2Fa1cdfb94-0ddb-40ae-9a09-ba6d1cb1cde1%2F2uml22.png&w=3840&q=75)
Transcribed Image Text:The variance of h(X) is the expected value of the squared difference between h(X) and its expected value.
V[h(X)] = 0ncx? =E {n(x) – Elh(x)]}² · p(x)
D.
Use this definition to find V(ax + b). [Hint: With h(X) = ax + b, E[h(X)] = aµ + b where u = E(X).]
(ax + b - E[ax + b])² · p(x) = L(
- Elax)"p«)
E[ax]
- ([
- (L
L(x - E(X))²p(x)
II
II
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