What is the significance of Level of Confidence ( alpha ) in statistics?

The confidence level describes the uncertainty associated with a sampling method. Suppose we used the same sampling method (say sample mean) to compute a different interval estimate for each sample. Some interval estimates would include the true population parameter and some would not.

With respect to estimation problems, alpha refers to the likelihood that the true population parameter lies outside the confidence interval. Alpha is usually expressed as a proportion. Thus, if the confidence level is 95%, then alpha would equal 1 - 0.95 or 0.05.

Constructing a Confidence Interval:

Constructing a confidence interval involves 4 steps.

Step 1: Identify the sample problem. Choose the statistic (like sample mean, etc) that
you will use to estimate population parameters.

Step 2: Select a confidence level. (Usually, it is 90%, 95% or 99%)

Step 3: Find the margin of error. (Usually given) If not given, use the following formula:-
Margin of error = Critical value * Standard deviation

Step 4: Specify the confidence interval. The uncertainty is denoted by the confidence level.
And the range of the confidence interval is defined