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[DOC File]UNDERSTANDING THE PEARSON CORRELATION …
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coefficient of determination, like the coefficient of correlation, describes the strength of a relationship, but has a more concrete interpretation. . SST. is the total sum of squared deviations about . SSE. is the total sum of squared deviations about the regression line . . SSR. is the total sum of squared deviations due to regression, i.e.
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[DOC File]STAT 515 -- Chapter 11: Regression
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Interpretation: An r2 of .98 means that the sum of squares of deviations of the y values about their predicted values has been reduced 98% by the use of the least squares equation = -2.2 + 2.3x, instead of , to predict y. The coefficient of determination is a number between 0 and 1, inclusive.
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[DOC File]Correlation and Regression
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The multiple coefficient of determination is. a. 0.333. b. 0.275. c. 0.300. d. 0.75. 2. In a multiple regression analysis involving 15 independent variables and 200 observations, SST = 800 and SSE = 240. The coefficient of determination is ... The interpretation of the coefficient on X1 is that.
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[DOC File]Regression Analysis (Simple)
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The square of the correlation coefficient is called the coefficient of determination, R2. Interpretation: R2 represents the proportion of sample variability in Y that is explained by its linear relationship with X. (R2 always between 0 and 1) For the Rockwell hardness / Young’s modulus data example, R2 = Interpretation: For the reflux ratio ...
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[DOCX File]CHAPTER
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Rule of Thumb for Interpreting the Size of a Correlation Coefficient Size of Correlation Interpretation .90 to 1.00 (-.90 to –1.00) Very high positive (negative) correlation .70 to .90 (-.70 to -.90) High positive (negative) correlation .50 to .70 (-.50 to -.70) Moderate positive (negative) correlation .30 to .50 (-.30 to -.50) Low positive (negative) correlation .00 to .30 (.00 to -.30 ...
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[DOC File]Adequacy of Regression Models
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In other words, the square of the correlation coefficient equals the proportion of the total variance in Y that can be associated with the variance in X. The square of the correlation coefficient is called the coefficient of determination. Conducting Pearson Correlation Coefficients. 1. Open the data file. 2. Click . Analyze ( Correlate. then ...
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[DOC File]Rule of Thumb for Interpreting the Size of a Correlation ...
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Prior to the interpretation of the prediction equation, one needs to consider the adequacy of the fit. This is done by the evaluation of the coefficient of determination. Having answered the adequacy question based on coefficient of determination, one might think that the regression coefficient estimates must be close to the true parameter values.
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Coefficient of Determination: Definition
r2 (Coefficient of Determination) = = Interpretation: 98% of the total sample variation in y is explained by the straight-line relationship between y and x, with the total sample variation in y being measured by the sum of squares of deviations of the sample y values about their mean .
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[DOC File]Correlation and Regression
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R2, or the coefficient of determination, is defined as the percent of variation in Y about it’s mean that is explained by the linear influence of the variation of X. Mathematically it is described by: R2 = SSD/TSS and will range between 0 and 1. Closer to one is a poorer model, closer to one is a better model.
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[DOC File]CHAPTER FIFTEEN
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correlation coefficient, r, its interpretation, the issue of correlation and cause and effect. least squares line and its use in modelling linear associations. data transformation and its purpose. Key skills. ... calculate the coefficient of determination, r. 2, and interpret in the context of the association being modelled and use the model to ...
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Coefficient of determination interpretation