Search results

  1. R

    Why is there n-1 degrees of freedom and not n-2 (student distribution)

    That makes sense to me. I think I'm beginning to understand, thank you very much for your answers. A quick question though: why are the degrees of freedom associated with the variance estimate? Is it linked to the definition of a "degree of freedom"? Maybe you can use this example to explain me...
  2. R

    Why is there n-1 degrees of freedom and not n-2 (student distribution)

    Aren't the mean and the variance dependent?
  3. R

    Why is there n-1 degrees of freedom and not n-2 (student distribution)

    I was until I read your comment .. :(
  4. R

    Why is there n-1 degrees of freedom and not n-2 (student distribution)

    Because they are independent, you should lose 2 degrees of freedom (two independent pieces of information)? If they were dependant, I would understand n-1. Sorry if I really don't understand
  5. R

    Why is there n-1 degrees of freedom and not n-2 (student distribution)

    I think this is different; my case is when the standard deviation is estimated and therefore not known. Of course when the standard deviation is known, a Z-test should be used.
  6. R

    Why is there n-1 degrees of freedom and not n-2 (student distribution)

    That is exactly my "problem" and I feel like I'm not convinced why it is n-1
  7. R

    Why is there n-1 degrees of freedom and not n-2 (student distribution)

    My reasoning was: you estimate 2 values so you lose 2 degrees of freedom. I know it is wrong but I'm still not convinced of why.
  8. R

    Why is there n-1 degrees of freedom and not n-2 (student distribution)

    Hi, So if I understand well, this statement is wrong? "Why do we have n-1 degrees of freedom? The reason is because to calculate the test statistic, we have used the sample mean as an estimator for the population mean µ"
  9. R

    Why is there n-1 degrees of freedom and not n-2 (student distribution)

    Yes I understand that the variance has n-1 degrees of freedom because of the estimation of the sample mean. BUT the t-distribution uses the estimate of the sample variance, which should remove ANOTHER degree of freedom? I hope my misunderstanding is clear enough?
  10. R

    Why is there n-1 degrees of freedom and not n-2 (student distribution)

    Hi, thanks for replying. But, what's different between estimating this one parameter (sample mean) and estimating the sample variance?
  11. R

    Why is there n-1 degrees of freedom and not n-2 (student distribution)

    When we want to compute a confidence interval for the mean of a sample of n persons, it is always explained that the number of degrees of freedom used should be equal to the sample size minus the number of estimated parameters. But, in my opinion, two parameters are estimated: the mean is...