how to calculate point estimate
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In statistics, point estimation involves the use of sampledata to calculate a single value (known as a statistic) which is to serve as a "best guess" for an unknown (fixed or random) population parameter.
More formally, it is the application of a point estimator to the data.
In general, point estimation should be contrasted with interval estimation.
Point estimation should be contrasted with general Bayesian methods of estimation, where the goal is usually to compute (perhaps to an approximation) the posterior distributions of parameters and other quantities of interest. The contrast here is between estimating a single point (point estimation), versus estimating a weighted set of points (a probability density function). However, where appropriate, Bayesian methodology can include the calculation of point estimates, either as the expectation or median of the posterior distribution or as the mode of this distribution.
Routes to deriving point estimates directly
- maximum likelihood (ML)
- method of moments, generalized method of moments
- minimum mean squared error (MMSE)
- minimum variance unbiased estimator (MVUE)
- best linear unbiased estimator (BLUE)
Routes to deriving point estimates via Bayesian Analysis
Properties of Point estimates
From Yahoo Answers
Answers:The point estimate is always the number in the middle: here, 14.
Answers:A point estimate is a sample statistic that estimates a population parameter. For example, the sample mean is a point estimate of the population mean. For what population parameter do you wish a point estimate for in this problem?
Answers:ANSWER: 60% = (300/500) * 100
Answers:Usually square roots are expressed as SquareRoot or SqrRt. You should memorize the squares. The nearest square to 18 is 4*4=16 So now you know the number is atleast bigger than 4. so you try 5*5=25 So you know the number is some digit between 4 and 5. so 4.xx Now try it with the other ones and than whip out a calculator and try it.