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[DOC File]DISCUSS regression and correlation
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The coefficient of determination, r2, is the % of the variability (as measured by the sum of the squared residuals) explained by the regression line. ( Correlation The Pearson correlation coefficient, r. Correlation is perfect when r = ( 1, strong when r is greater than 0.8 in size, and weak when r is less than 0.5 in size. ( More correlation
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[DOC File]Correlation and Regression
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Correlation and Regression. How can we explore the relationship between two quantitative variables? Graphically, we can construct a scatterplot. Numerically, we can calculate a correlation coefficient and a regression equation. Correlation. The Pearson correlation coefficient, r, measures the . strength. and the . direction. of a straight-line ...
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[DOC File]S.ID.B.6.Regression2.doc
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State the linear regression equation represented by the data table when is used to represent the year 2007 and y is used to represent the attendance. Round all values to the nearest hundredth. State the correlation coefficient to the nearest hundredth and determine whether the data suggest a strong or weak association.
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[DOC File]Correlation and Simple Regression
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The correlation coefficient can also be expressed as the mean of the products of the standardized scores. Later, in regression, this becomes a useful perception because regression with standardized scores/variables is simpler to interpret. The . Population Correlation Coefficient . is symbolized as the small Greek letter ρ (rho).
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[DOC File]CHAPTER 17: SOCIAL STATISTICS
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a. A path coefficient. b. A partial epsilon. c. A coefficient of alienation. d. Residual variance. e. A variance coefficient. 20. Which of the following regression equations represents the strongest relationship between X and Y? a. Y = 2 + .3X. b. Y = 2 + 1.3X. c. Y = 2 + 1.8X. d. Y = 2 + 3X. e. The strength of the relationship cannot be ...
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[DOC File]Correlation and Regression
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The coefficient of determination is a number between 0 and 1, inclusive. That is, If r2 = 0, the least squares regression line has no explanatory value. If r2 = 1, the least-squares regression line explains 100% of the variation in the response variable.
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[DOC File]Rule of Thumb for Interpreting the Size of a Correlation ...
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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]S.ID.C.8.CorrelationCoefficient.doc - JMAP
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Based on this linear regression model, the correlation coefficient could be. 1) between and 0 3) equal to 2) between 0 and 1 4) equal to 0 18 A linear regression equation of best fit between a student’s attendance and the degree of success in school is . The correlation coefficient, r, for …
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[DOCX File]Chapter Seven: Correlation and Regression
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The correlation coefficient may range from -1 to 1, where -1 or 1 indicates a “perfect” relationship. The further the coefficient is from 0, regardless of whether it is positive or negative, the stronger the relationship between the two variables. Thus, a coefficient of .453 is exactly as strong as a coefficient …
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[DOCX File]Chapter Seven: Correlation and Regression
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The correlation coefficient may range from -1 to 1, where -1 or 1 indicates a “perfect” relationship. The further the coefficient is from 0, regardless of whether it is positive or negative, the stronger the relationship between the two variables. Thus, a coefficient of .467 is exactly as strong as a coefficient of -.467. Positive coefficients
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What is a strong regression coefficient