Course Content
Probability Theory Mastering
Probability Theory Mastering
Challenge: Estimate Parameters of Chi-square Distribution
Task
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:
- Calculate the mean value over samples using
.mean()
method. - Use
.fit()
method to get maximum likelihood estimation for the parameter.
Thanks for your feedback!
Challenge: Estimate Parameters of Chi-square Distribution
Task
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:
- Calculate the mean value over samples using
.mean()
method. - Use
.fit()
method to get maximum likelihood estimation for the parameter.
Thanks for your feedback!
Challenge: Estimate Parameters of Chi-square Distribution
Task
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:
- Calculate the mean value over samples using
.mean()
method. - Use
.fit()
method to get maximum likelihood estimation for the parameter.
Thanks for your feedback!
Task
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:
- Calculate the mean value over samples using
.mean()
method. - Use
.fit()
method to get maximum likelihood estimation for the parameter.