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For the terms below, select the best descriptions from the list. 4 v 1 v 3 V 2 > Coefficient of Determination (²) Sum of the Square of the Totals (SST) Standard Error of the Estimate (se) Sum of the Square of the Residuals (SSR) 1. 2. 3. 4. 5. sum of the squared differences between the observed variable and its mean. sum of the squared differences between the predicted variable (i.e., the variable's regression line) and its observed values. average distance from which the observed values fall from their predicted variable (i.e., the variable's regression line) line. The "comparative accuracy" or "skill" of a non-trivial method of estimating a value when compared against an unskilled method. The number of members in a sample that can vary without changing the outcome.

For the terms below, select the best descriptions from the list. 4 v 1 v 3 V 2 > Coefficient of Determination (²) Sum of the Square of the Totals (SST) Standard Error of the Estimate (se) Sum of the Square of the Residuals (SSR) 1. 2. 3. 4. 5. sum of the squared differences between the observed variable and its mean. sum of the squared differences between the predicted variable (i.e., the variable's regression line) and its observed values. average distance from which the observed values fall from their predicted variable (i.e., the variable's regression line) line. The "comparative accuracy" or "skill" of a non-trivial method of estimating a value when compared against an unskilled method. The number of members in a sample that can vary without changing the outcome.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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For the terms below, select the best descriptions from the list. 4 v 1 3 2 < > Coefficient of Determination (²) Sum of the Square of the Totals (SST) Standard Error of the Estimate (se) Sum of the Square of the Residuals (SSR) 1. sum of the squared differences between the observed variable and its mean. 2. 3. 4. 5. sum of the squared differences between the predicted variable (i.e., the variable's regression line) and its observed values. average distance from which the observed values fall from their predicted variable (i.e., the variable's regression line) line. The "comparative accuracy" or "skill" of a non-trivial method of estimating a value when compared against an unskilled method. The number of members in a sample that can vary without changing the outcome.
Transcribed Image Text:For the terms below, select the best descriptions from the list. 4 v 1 3 2 < > Coefficient of Determination (²) Sum of the Square of the Totals (SST) Standard Error of the Estimate (se) Sum of the Square of the Residuals (SSR) 1. sum of the squared differences between the observed variable and its mean. 2. 3. 4. 5. sum of the squared differences between the predicted variable (i.e., the variable's regression line) and its observed values. average distance from which the observed values fall from their predicted variable (i.e., the variable's regression line) line. The "comparative accuracy" or "skill" of a non-trivial method of estimating a value when compared against an unskilled method. The number of members in a sample that can vary without changing the outcome.
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