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Challenge: Estimate Parameters of Chi-square Distribution | Estimation of Population Parameters
Advanced Probability Theory
course content

Conteúdo do Curso

Advanced Probability Theory

Advanced Probability Theory

1. Additional Statements From The Probability Theory
2. The Limit Theorems of Probability Theory
3. Estimation of Population Parameters
4. Testing of Statistical Hypotheses

bookChallenge: Estimate Parameters of Chi-square Distribution

Tarefa
test

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Suppose that we have samples from the Chi-square distribution. We must determine the parameter K of this distribution, which represents the number of degrees of freedom.
We know that the mathematical expectation of the Chi-square distributes value is equal to this parameter K.
Estimate this parameter using the method of moments and the maximum likelihood method. Since the number of degrees of freedom can only be discrete, round the resulting number to the nearest integer.
Your task is:

  1. Calculate the mean value over samples using .mean() method.
  2. Use .fit() method to get maximum likelihood estimation for the parameter.

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Seção 3. Capítulo 3
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bookChallenge: Estimate Parameters of Chi-square Distribution

Tarefa
test

Swipe to show code editor

Suppose that we have samples from the Chi-square distribution. We must determine the parameter K of this distribution, which represents the number of degrees of freedom.
We know that the mathematical expectation of the Chi-square distributes value is equal to this parameter K.
Estimate this parameter using the method of moments and the maximum likelihood method. Since the number of degrees of freedom can only be discrete, round the resulting number to the nearest integer.
Your task is:

  1. Calculate the mean value over samples using .mean() method.
  2. Use .fit() method to get maximum likelihood estimation for the parameter.

Switch to desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Tudo estava claro?

Como podemos melhorá-lo?

Obrigado pelo seu feedback!

Seção 3. Capítulo 3
toggle bottom row

bookChallenge: Estimate Parameters of Chi-square Distribution

Tarefa
test

Swipe to show code editor

Suppose that we have samples from the Chi-square distribution. We must determine the parameter K of this distribution, which represents the number of degrees of freedom.
We know that the mathematical expectation of the Chi-square distributes value is equal to this parameter K.
Estimate this parameter using the method of moments and the maximum likelihood method. Since the number of degrees of freedom can only be discrete, round the resulting number to the nearest integer.
Your task is:

  1. Calculate the mean value over samples using .mean() method.
  2. Use .fit() method to get maximum likelihood estimation for the parameter.

Switch to desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Tudo estava claro?

Como podemos melhorá-lo?

Obrigado pelo seu feedback!

Tarefa
test

Swipe to show code editor

Suppose that we have samples from the Chi-square distribution. We must determine the parameter K of this distribution, which represents the number of degrees of freedom.
We know that the mathematical expectation of the Chi-square distributes value is equal to this parameter K.
Estimate this parameter using the method of moments and the maximum likelihood method. Since the number of degrees of freedom can only be discrete, round the resulting number to the nearest integer.
Your task is:

  1. Calculate the mean value over samples using .mean() method.
  2. Use .fit() method to get maximum likelihood estimation for the parameter.

Switch to desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Seção 3. Capítulo 3
Switch to desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
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