What is point estimation - Definition and Meaning
Point Estimation :
Point estimation is the procedure of defining a single estimated value of the parameter of given population.
Formula :
MLE = S / T
Laplace = (S+1) / (T+2)
Jeffrey = (S+0.5) / (T+1)
Wilson = (S+(z2/2)) / (T+z2)
Where,
MLE = Maximum Likelihood Estimation
S = Number of Success
T = Number of Trials
z = Z-Critical Value
Best Point Estimation Rules :
1. MLE<=0.5 --> Wilson Estimation
2. Between MLE>0.5 and MLE<0.9 --> MLE
3. MLE>0.9 --> either Laplace or Jeffrey based on
which is small
Example :
Success (S) = 4
Trials (T) = 9
Confidence Interval (P) = 99%
MLE = 4/9 = 0.4444
Laplace = 5/11 = 0.4545
Jeffery = 4.5/10 = 0.45
z = from z score table of 99% level = 2.5758
Wilson = (4+(2.57582/2)) / (9+2.57582) = 0.468
Best Point:
MLE<0.5
so, best point = Wilson Estimation = 0.468
Learn what is point estimation. Also find the definition and meaning for various math words from this math dictionary.
