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Parameters of a probability distribution, such as the mean and standard deviation of a normal distribution
Regression coefficients of a regression model, such as Y=a'X
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Engineers apply parameter estimation to dynamic models to compute:
Coefficients of transfer functions, including ARX, ARMAX, Box-Jenkins, and output-error models
Entries in state-space matrices
Coefficients of ODEs or well-structured systems with parameter constraints (grey-box system identification).
Regression coefficients, saturation levels, or dead-zone limits for nonlinear dynamic systems, including nonlinear ARX and Hammerstein-Wi.ener
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For both continuous variables (e.g., population mean) and dichotomous variables (e.g., population proportion) one first computes the point estimate from a sample.
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The process of finding an approximate value of some parameter—such as the mean (average)—of a population from random samples of the population.
It is the value of statistic that estimates the value of a parameter.
The sample standard deviation (s) is a point estimate of the population standard deviation (σ).
The sample mean (̄x) is a point estimate of the population mean, μ.
The sample variance (s2) is a point estimate of the population variance (σ2).
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Range of values you expect your estimate to fall between if you redo your test, within certain level of confidence.
Confidence-Describes - Probability
Point Estimate +- Margin of error
Given : ( α = 0.05 , n ,x̄ , Population standard deviation σ )
Tests:
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Population standard is given & n >= 30.
Point Estimate +- Margin of error
x̄ +- z α/2 (σ/ √ n )
Upper Bound - x̄ + z α/2 (σ/ √ n ) = ztable(Answer)
Lower Bound - x̄ - z α/2 (σ/ √ n )=ztable(Answer)
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Population standard deviation is not given & n >≠ 30.
Point Estimate +- Margin of error
x̄ +- z α/2 (σ/ √ n )
t = degree of freedom= n-1
Upper Bound - x̄ + t α/2 (s/ √ n ) = t table(Answer)
Lower Bound - x̄ - t α/2 (s / √ n )=t table(Answer)
(s / √ n ) is Standard error
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The standard error is the standard deviation of a sample population. It measures the accuracy with which a sample represents a population.
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Degrees of freedom, often represented by v or df, is the number of independent pieces of information used to calculate a statistic.
It’s calculated as the sample size minus the number of restrictions.
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Suppose you randomly sample 10 American adults and measure their daily calcium intake. You use a one-sample t test to determine whether the mean daily intake of American adults is equal to the recommended amount of 1000 mg.The test statistic, t, has 9 degrees of freedom:
df = n − 1
df = 10 − 1
df = 9
You calculate a t value of 1.41 for the sample, which corresponds to a p value of .19. You report your results:
“The participants’ mean daily calcium intake did not differ from the recommended amount of 1000 mg, t(9) = 1.41, p = 0.19.”
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IDEAS CURATED BY
CURATOR'S NOTE
Parameter estimation is the process of computing a model’s parameter values from measured data. You can apply parameter estimation to different types of mathematical models, including statistical models, parametric dynamic models, and data-based Simulink® models
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