The point estimate calculator determines the best point estimate based on the number of successes, trials, and confidence level.

- First, input the number of successes and trials.
- Enter the confidence level in terms of percentage.
- Now press the 'Calculate' button to obtain the results.
- Finally, the tool returns the best point estimate including Maximum Likelihood (MLE), Wilson, Jeffrey, and Laplace point estimates.

The calculator uses the following formulas to compute the point estimate of a population proportion:

**Maximum Likelihood Estimate (MLE)**: x / n

**Wilson**: (x + z^{2}/2) / (n + z^{2})

**Jeffrey**: (x + 0.5) / (n + 1)

**Laplace**: (x + 1) / (n + 2)

Where,

x = Number of successes,

n = Number of trials or sample size,

z = Z-score associated with the confidence level.

The tool uses the following logic to determine the most suitable point estimate:

If x/n ≤ 0.5, the Wilson Point Estimate is applied.

If 0.5 < x/n < 0.9, the MLE Point Estimate is applied.

If 0.9 ≤ x/n < 1, the smallest value of the Laplace or Jeffreys Point Estimate is applied.

If x/n = 1.0, the Laplace Point Estimate is applied.