MLE Mastery

Froggy Jumps

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Test your MLE knowledge

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Samah

Saudi Arabia

Download the paper version to play

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Froggy Jumps MLE MasteryOnline version Test your MLE knowledge by Samah 1 What does MLE stand for in statistics? a Maximum Likelihood Estimator b Maximum Likelihood Experiment c Mean Least Error 2 Which function is maximized to obtain the MLE? a Log-likelihood function b Posterior probability c Likelihood ratio 3 Which condition helps ensure the MLE is consistent as sample size grows? a Finite population assumption b Regularity conditions c Bayesian prior 4 In a normal model with unknown mean and known variance, the MLE of the mean is: a Mode of data b Sample mean c Sample median 5 What is the derivative method commonly used to find MLEs? a Differentiate the posterior b Maximize the prior c Set the score function to zero 6 MLE is invariant under monotone transformations. What does this mean? a MLE changes with data scale b MLE of g(theta) is g(MLE of theta) c MLE requires re-estimation for g(theta) 7 Which quantity often measures the precision of an MLE? a Fisher information b Bayes factor c P-value 8 If theta_hat is the MLE, what is its asymptotic distribution under regularity? a Normal with variance 1/I(theta) b Uniform c Cauchy 9 When data are i.i.d., the MLE tends to: a Minimize the likelihood b Be equal to the sample median c Maximize the joint likelihood 10 Which of the following is a common alternative to MLE for parameter estimation? a Method of moments b Bayesian refusal c Maximum a priori

Froggy Jumps

MLE MasteryOnline version

Test your MLE knowledge

by Samah

What does MLE stand for in statistics?

Maximum Likelihood Estimator

Maximum Likelihood Experiment

Mean Least Error

Which function is maximized to obtain the MLE?

Log-likelihood function

Posterior probability

Likelihood ratio

Which condition helps ensure the MLE is consistent as sample size grows?

Finite population assumption

Regularity conditions

Bayesian prior

In a normal model with unknown mean and known variance, the MLE of the mean is:

Mode of data

Sample mean

Sample median

What is the derivative method commonly used to find MLEs?

Differentiate the posterior

Maximize the prior

Set the score function to zero

MLE is invariant under monotone transformations. What does this mean?

MLE changes with data scale

MLE of g(theta) is g(MLE of theta)

MLE requires re-estimation for g(theta)

Which quantity often measures the precision of an MLE?

Fisher information

Bayes factor

P-value

If theta_hat is the MLE, what is its asymptotic distribution under regularity?

Normal with variance 1/I(theta)

Uniform

Cauchy

When data are i.i.d., the MLE tends to:

Minimize the likelihood

Be equal to the sample median

Maximize the joint likelihood

Which of the following is a common alternative to MLE for parameter estimation?

Method of moments

Bayesian refusal

Maximum a priori

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MLE Mastery

Froggy Jumps

About this activity

Created by

Download the paper version to play

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MLE MasteryOnline version

by Samah

What does MLE stand for in statistics?

Which function is maximized to obtain the MLE?

Which condition helps ensure the MLE is consistent as sample size grows?

In a normal model with unknown mean and known variance, the MLE of the mean is:

What is the derivative method commonly used to find MLEs?

MLE is invariant under monotone transformations. What does this mean?

Which quantity often measures the precision of an MLE?

If theta_hat is the MLE, what is its asymptotic distribution under regularity?

When data are i.i.d., the MLE tends to:

Which of the following is a common alternative to MLE for parameter estimation?

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