Compute the total variation distance between
Inverse Normal Distribution
The method used for finding the corresponding z-critical value in a normal distribution using the known probability is said to be an inverse normal distribution. The inverse normal distribution is a continuous probability distribution with a family of two parameters.
Mean, Median, Mode
It is a descriptive summary of a data set. It can be defined by using some of the measures. The central tendencies do not provide information regarding individual data from the dataset. However, they give a summary of the data set. The central tendency or measure of central tendency is a central or typical value for a probability distribution.
Z-Scores
A z-score is a unit of measurement used in statistics to describe the position of a raw score in terms of its distance from the mean, measured with reference to standard deviation from the mean. Z-scores are useful in statistics because they allow comparison between two scores that belong to different normal distributions.
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![Compute the total variation distance between
P = Ber (p)
and Q = Ber (g), where p, q € [0, 1] .
(If applicable, enter abs(x) for |æ|.)
TV (P, Q) =
Let X1....,X, be n i.i.d. Bernoulli random variables with some parameter p e [0,1], and X, be their empirical average. Consider the total
variation distance TV (Ber (X,), Ber (p))between Ber (X) and Ber (p) as a function of the random variable Xm, and hence a random variable itself.
Does TV (Ber (X), Ber (p)) necessarily converge in probability to a constant? If yes, enter the constant below; if not; enter DNE.
(P)
TV (Ber (X,), Ber (p))
n00
STANDARD NOTATION](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F45ec0afe-b7c9-45c8-bd67-2221f08741f3%2F0cb0bf70-c893-440b-aa0e-5138fb31b9d4%2Fuxzwzp_processed.png&w=3840&q=75)
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