II. B. 2. Statistical Interval Estimates

Confidence intervals (CIs)provide a means to judge point estimates based on a sample from the population.

If that statement excites you, you may well have the makings of a fine statistician.

CIs are a form of internal estimate and specify a range within which a parameter may reside. CIs helps us evaluate the trustworthiness of point estimates. [Read more…]

Edited by John Healy

There are a number of different methods to calculate confidence intervals for a proportion. The normal approximation method is easy to use and is appropriate in most cases.

Clopper and Pearson describe the Clopper-Pearson method also called the exact confidence interval and we’ll describe it in a separate article.

There are other methods, which again will find a description in separate articles. [Read more…]

EDITED BY JOHN HEALY

As with other point estimates, we often want to calculate the confidence interval about the estimate. The intent is to determine the range of reasonable values for the true and unknown population parameter. For MTBF, this no different.

[Read more…]

When using a sample to calculate a statistic we are estimating a population parameter. It is just an estimate and the sample due to the nature of drawing a sample may not create a value (statistic) that is close to the actual value (parameter). [Read more…]

A point estimate of the mean of a population is determined by calculating the mean of a sample drawn from the population. The calculation of the mean is the sum of all sample values divided by the number of values. [Read more…]