In statistics, point estimating uses sample data to determine a single value that will serve as the "best guess" or "best estimate" of an unidentified population parameter.
It is called a point estimate because it identifies a point in some parameter space (for example, the population mean). More precisely, it is the process of applying a point estimator to the data in order to produce a point estimate.
Point estimation can be compared with interval estimation, where the interval estimates are typically either credible intervals or confidence intervals depending on whether frequentist or Bayesian inference is being used. A point estimator can be compared to a set estimator more generically.
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A random sample of 78 students were interviewed and 59 said they would vote fore a democrat in the 2008 election. 1. Let p represent the proportion of all students at this college who will vote for a democrat. Find a point estimate p for p.