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[DOC File]DATA CORR_EG;
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correlation coefficients. that describe how well a straight line fits the data. If your plot shows that the line that relates X and Y is linear, you should use the ... Pearson. correlation coefficient discussed below. If the plot shows that the relationship is monotonic (not a straight line, but a line whose slope is always positive or always ...
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[DOC File]Comparing Correlation Coefficients, Slopes, and Intercepts
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Do not draw causal inferences from a correlation. X ( Y Y ( X. example: r = -.30 #friends, depression. r = +.40 hours studying, grades Causal inferences require an “experiment” V. Other Correlation Coefficients. Pearson r. used when X & Y are at least interval level. Many types of correlation coefficients for other data. Spearman ( ordinal ...
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Pearson correlation coefficient - Wikipedia
The Pearson product-moment correlation coefficient (r) assesses the degree that quantitative variables are linearly related in a sample. Each individual or case must have scores on two quantitative variables (i.e., continuous variables measured on the interval or ratio scales).
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[DOC File]Rule of Thumb for Interpreting the Size of a Correlation ...
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Comparing Correlation Coefficients, Slopes, and Intercepts(Two Independent Samples. H(: (1 = (2. ... On the right, we can see that the slope is clearly higher with the red x’s than with the blue o’s, but the Pearson r is about the same for both sets of data. We can predict equally well in both groups, but the Y variable increases much more ...
interpreting pearson's correlation

[DOCX File]Bivariate Linear Correlation
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Nomiss is for listwise deletion of missing values (as opposed to the default option of pairwise deletion), while Spearman is a non-parametric test of correlation (Pearson correlation assumes normality). proc. corr. data = cars2 nomiss; var weight year mpg; run; Pearson Correlation Coefficients, N = 397. Prob > |r| under H0: Rho=0
interpreting correlation coefficient

[DOC File]BIVARIATE CORRELATION
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Pearson Partial Correlation Coefficients, N = 6. Prob > |r| under H0: Partial Rho=0. HEIGHT WEIGHT. HEIGHT 1.00000 0.91934. 0.0272 WEIGHT 0.91934 1.00000. 0.0272 PROC REG DATA=CORR_EG; TITLE "REGRESSION LINE FOR HEIGHT-WEIGHT DATA"; MODEL WEIGHT=HEIGHT; RUN; REGRESSION LINE FOR HEIGHT-WEIGHT DATA 4 ...
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[DOC File]UNDERSTANDING THE PEARSON CORRELATION …
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Matrix Showing Correlation Coefficients Appropriate for Scales of Measurement for Variable X and Variable Y. Variable X Nominal Ordinal Interval/Ratio Variable Y Nominal Phi (() C coefficient. Cramer’s V ( and ((Rank-biserial Point-biserial Ordinal Rank-biserial. Tetrachoric. Spearman (Biseral Interval/Ratio Point-biserial. Biserial rb Pearson r
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Pearson correlation coefficients in r