Point estimation involves the use of sample data to calculate a single value (known as a statistic) which is to serve as a “best guess” or “best estimate” of an unknown (fixed or random) population parameter. More formally, it is the application of a point estimator to the data.
· MLEMLE = Maximum Likelihood Estimation.
· SS = Number of Success .
· TT = Number of trials.
· zz = Z-Critical Value.
If a coin is tossed 4 times out of nine trials in 99% confidence interval level, then what is the best point of success of that coin?
Success(S) = 4 Trials (T) = 9 Confidence Interval Level (P) = 99% = 0.99. In order to compute best point estimation, let compute all the values:
Discover Z-Critical Value from Z table. Z-Critical Value (z) = for 99% level = 2.5758
Accordingly the Best Point Estimation is 0.468 as MLE ≤ 0.5