the regression errors and regression residuals and where they lead to the concept of studentized residuals. In econometrics, "errors" are also called...

statistics, the residual sum of squares (RSS), also known as the sum of squared residuals (SSR) or the sum of squared estimate of errors (SSE), is the sum...

least absolute errors (LAE), least absolute residuals (LAR), or least absolute values (LAV), is a statistical optimality criterion and a statistical optimization...

variances of the errors at these different input variable values are equal. The issue is the difference between errors and residuals in statistics, particularly...

attributed to such errors, they are "errors" in the sense in which that term is used in statistics; see errors and residuals in statistics. Every time a measurement...

(and are therefore always in reference to an estimate) and are called errors (or prediction errors) when computed out-of-sample (aka on the full set, referencing...

population of all possible observations, the residuals should belong to a Student's t-distribution. Studentized residuals are useful in making a statistical test...

appropriate rejection of a false null hypothesis. Type I errors can be thought of as errors of commission, in which the status quo is erroneously rejected...

(see errors and residuals in statistics for more details). Although the MSE (as defined in this article) is not an unbiased estimator of the error variance...

error in medicine is used as a label for nearly all of the clinical incidents that harm patients. Medical errors are often described as human errors in...

necessary to confirm suspicions of misconduct. Error analysis (linguistics) Error bar Errors and residuals in statistics Propagation of uncertainty Validated...

uncertainty (or propagation of error) is the effect of variables' uncertainties (or errors, more specifically random errors) on the uncertainty of a function...

the case, the errors are said to be heteroskedastic, or to have heteroskedasticity, and this behaviour will be reflected in the residuals u ^ i {\textstyle...

Clustered standard errors (or Liang-Zeger standard errors) are measurements that estimate the standard error of a regression parameter in settings where...

"disturbance", "noise" or simply "error" (will be contrasted with "residual" later in the article; see errors and residuals in statistics). Note that to include...

autocorrelation at lag 1 in the residuals (prediction errors) from a regression analysis. It is named after James Durbin and Geoffrey Watson. The small sample...

of residuals against time drift in the errors (data collected over time): run charts of the response and errors versus time independence of errors: lag...

E(e_{i}|X_{i})=0} The variance of the residuals e i {\displaystyle e_{i}} is constant across observations (homoscedasticity). The residuals e i {\displaystyle e_{i}}...

these range errors must be multiplied by the appropriate dilution of precision terms and then RSS'ed with the numerical error. Electronics errors are one...

In statistics, sampling errors are incurred when the statistical characteristics of a population are estimated from a subset, or sample, of that population...

Linearity: Relationship between each predictor and outcome must be linear 2. Normality of residuals: Residuals should follow a normal distribution 3. Homoscedasticity:...

context of errors and residuals, the "hat" over the letter ε ^ {\displaystyle {\hat {\varepsilon }}} indicates an observable estimate (the residuals) of an...

of variability in the residuals for different levels of the explanatory variables suggests possible heteroscedasticity. Residuals against explanatory variables...

algorithms a residual frame is formed by subtracting the reference frame from the desired frame. This difference is known as the error or residual frame. The...

The notation for standard error can be any one of SE, SEM (for standard error of measurement or mean), or SE. Standard errors provide simple measures of...

curve is often assumed to be that which minimizes the sum of squared residuals. This is the ordinary least squares (OLS) approach. However, in cases...

In statistics, mean absolute error (MAE) is a measure of errors between paired observations expressing the same phenomenon. Examples of Y versus X include...

Error rate, meaning the frequency of errors, can have the following uses: Bayes error rate Bit error rate Per-comparison error rate Residual bit error...

Accepted and experimental value Condition number Errors and residuals in statistics Experimental uncertainty analysis Machine epsilon Measurement error Measurement...

square deviation Errors and residuals in statistics Khan, Aman U.; Hildreth, W. Bartley (2003). Case studies in public budgeting and financial management...