00:01
When we compute a 90 % confidence interval for a parameter, in this case we are computing for the population mean, this confidence level means that if i compute 100 confidence intervals, 90 % of them will contain the true value of the parameter, mu.
00:26
So considering the interpretation of a 90 % confidence, interval that we mentioned.
00:33
We have that for each 100 intervals that we have, we should expect 90 % of them to contain the true value of the parameter.
00:44
So in this case, 90 % of 100 is 90.
00:47
So 19 of them will be, will contain the true parameter.
00:52
So since we have 500 intervals, because each student is computing one confidence interval here.
01:00
For the mule we have that if i separate this 500 in five batches of 100 intervals here and because of the interpretation for each of this 190 will have or will contain the two parameters here 90 90 and also for the last one so we should expect it in the end that we will have for all the batches that we have of 100 intervals, in this case five batches, 90 % in each of them will contain the two parameters, so in this case 90 intervals...