Sse ssr sst formulas

    • [DOC File]STATISTICS 302:504-505

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      SSE = 827 is the unexplained variation: measure of y's variation that can be attributed to an approximate linear relationship. SST = 8368.7 explains the deviations of y from the sample mean of y Coefficient of Determination, R2 : Measure what percent of Y's variation is explained by the X variables via the regression model.

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    • [DOC File]Derivation of the Ordinary Least Squares Estimator

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      Mathematically, this statement is SST = SSR + SSE. To show this equation holds, algebraic properties (1) and (3) derived earlier must be used. Using these two properties, and expanding the SST equation, the necessary steps to show this equation holds are shown in Table 3.

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    • [DOC File]Derivation of the Ordinary Least Squares Estimator

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      If X explains no variation in y, the SSE will equal zero. Looking at equation (15), if SSR = SST a value of zero for R2 is obtained. On the other hand, if X explains all the variation in y, SSR will equal zero. In this case, R2 equals one. The values of [0 - 1] are just the theoretical range for …

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    • [DOC File]Chapter 11 – Simple linear regression

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      Computational Formulas for Simple Linear Regression (Sec. 11-10) Normal Equations (Based on Minimizing SSE by Calculus) Computational Formula for the Slope, b1. Computational Formula for the Y-intercept, b0. Computational Formula for the Total Sum of Squares, SST. Computational Formula for the Regression Sum of Squares, SSR

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    • [DOC File]FORMULAS

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      Coefficient of Determination, R2 : Measure what percent of Y's variation is explained by the X variables via the regression model. It tells us the proportion of SST that is explained by the fitted equation. Note that SSE is the proportion of SST that is not explained by the model.

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    • [DOC File]Chapters 7 through 13 - The University of Tennessee at ...

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      Relationship among SST, SSR, and SSE. SST = SSR + SSE. Multiple Coefficient of Determination = Also. Adjusted Multiple Coefficient of Determination. Excel’s ANOVA Table. ANOVA df SS MS F Significance F Regression p SSR MSR = SSR/p F = MSR/MSE Residual n-p-1 SSE MSE = SSE/(n-p-1) Total n-1 SST CHAPTER FORMULAS (Continued)

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    • [DOC File]CHAPTER 11—REGRESSION/CORRELATION

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      Fact: Sum of Squares Total = Sum of Squares Regression + Sum of Squares Errors (SST) = (SSR) + (SSE) Proof: NOTE ( SST = SSR + SSE are “definitional” formulas. Computational and alternative forms for these SSQ’s, such as SSR = (B1)2SXX exist and are used in practice. The degrees of freedom of (SSQ’s) also partition.

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    • [DOCX File]Public opinion research companies are often interested in ...

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      (and the acronym SSR has another meaning in certain statistical analyses). As a formula, sum of the squared residuals = SSE = Σ ... The lower the value of SSE/SST, ... Notice that the SSE and SST formulas are identical when the predicted value of y (y ) is equal to the mean of the y …

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    • [DOC File]Chapters 1 through 13

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      Relationship among SST, SSR, and SSE. SST = SSR + SSE. Multiple Coefficient of Determination = Also. Adjusted Multiple Coefficient of Determination. Excel’s ANOVA Table. ANOVA df SS MS F Significance F Regression p SSR MSR = SSR/p F = MSR/MSE Residual n-p-1 SSE MSE = SSE/(n-p-1) Total n-1 SST CHAPTER FORMULAS (Continued)

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    • [DOC File]Economics 20 - Dartmouth College | Home

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      = SST = SSE = SSR. so that SST = SSE + SSR. The R2 is the fraction of the variation in y that is explained by the estimated model, and thus measures goodness of fit. It is defined as: R2 = SSE/SST = 1 – SSR/SST. The R2 can also be interpreted as the square of the correlation between y and ลท. Unbiasedness & Omitted Variable Bias

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