Let Y 1 , Y 2 , …, Y n be independent random variables, each with probability density function f ( y ) = { 3 y 2 , 0 ≤ y ≤ 1 , 0 , elsewhere . Show that Y ¯ converges in probability to some constant and find the constant.
Let Y 1 , Y 2 , …, Y n be independent random variables, each with probability density function f ( y ) = { 3 y 2 , 0 ≤ y ≤ 1 , 0 , elsewhere . Show that Y ¯ converges in probability to some constant and find the constant.
Let Y1, Y2, …, Yn be independent random variables, each with probability density function
f
(
y
)
=
{
3
y
2
,
0
≤
y
≤
1
,
0
,
elsewhere
.
Show that
Y
¯
converges in probability to some constant and find the constant.
Expression, rule, or law that gives the relationship between an independent variable and dependent variable. Some important types of functions are injective function, surjective function, polynomial function, and inverse function.
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Continuous Probability Distributions - Basic Introduction; Author: The Organic Chemistry Tutor;https://www.youtube.com/watch?v=QxqxdQ_g2uw;License: Standard YouTube License, CC-BY
Probability Density Function (p.d.f.) Finding k (Part 1) | ExamSolutions; Author: ExamSolutions;https://www.youtube.com/watch?v=RsuS2ehsTDM;License: Standard YouTube License, CC-BY
Find the value of k so that the Function is a Probability Density Function; Author: The Math Sorcerer;https://www.youtube.com/watch?v=QqoCZWrVnbA;License: Standard Youtube License