Estimation Task

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An estimation task is a data-driven prediction task that requires finding the sample statistic for a population parameter (mapped to an estimate of an estimand).



    1. The process of making an estimate.
  • (Wikipedia, 2016) ⇒ Retrieved:2016-1-9.
    • Estimation (or estimating) is the process of finding an estimate, or approximation, which is a value that is usable for some purpose even if input data may be incomplete, uncertain, or unstable. The value is nonetheless usable because it is derived from the best information available.[1] Typically, estimation involves "using the value of a statistic derived from a sample to estimate the value of a corresponding population parameter".[2] The sample provides information that can be projected, through various formal or informal processes, to determine a range most likely to describe the missing information. An estimate that turns out to be incorrect will be an overestimate if the estimate exceeded the actual result, [3] and an underestimate if the estimate fell short of the actual result. [4]
  1. C. Lon Enloe, Elizabeth Garnett, Jonathan Miles, Physical Science: What the Technology Professional Needs to Know (2000), p. 47.
  2. Raymond A. Kent, "Estimation", Data Construction and Data Analysis for Survey Research (2001), p. 157.
  3. James Tate, John Schoonbeck, Reviewing Mathematics (2003), page 27: "An overestimate is an estimate you know is greater than the exact answer".
  4. James Tate, John Schoonbeck, Reviewing Mathematics (2003), page 27: "An underestimate is an estimate you know is less than the exact answer".


    •  Estimation theory is a branch of statistics and signal processing that deals with estimating the values of parameters based on measured/empirical data that has a random component. The parameters describe an underlying physical setting in such a way that the value of the parameters affects the distribution of the measured data. An estimator attempts to approximate the unknown parameters using the measurements.