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Correlation

Correlation. Topics. Measure of Relationship Strength Direction Scatterplot Conceptual Formula Computational Formula Assumptions Problems Effecting the Interpretation of the Correlation Coefficient. Measure of Relationship.

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Correlation

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  1. Correlation

  2. Topics • Measure of Relationship • Strength • Direction • Scatterplot • Conceptual Formula • Computational Formula • Assumptions • Problems Effecting the Interpretation of the Correlation Coefficient

  3. Measure of Relationship • In a correlational study, two measures -- representing the variables of interest -- are given to onegroup of subjects. • The subject’s scores on both measures are summarized, and the relationship between the scores on the two measures is examined.

  4. Measure of Relationship • When the correlation coefficient is used to describe a linear relationship, the coefficient can take on values from -1.00 to +1.00. • The sign of the correlation indicates the direction of the relationship between two variables.

  5. Measure of Relationship • A positive relationship means that low scores on X go with low scores on Y whereas high scores on X go with high scores on Y. • A negative relationship means that as scores on X increase, scores on Y decrease. • The absolute magnitude or size of the correlation coefficient -- that is, ignoring the plus or minus sign -- indicates the strength of the relationship between X and Y.

  6. Measure of Relationship • A correlation of +.95 or of -.95 indicates a very strong relationship between the two variables. • A correlation of 0 indicates that there is no linear relationship between the variables. • Guilford's suggested interpretations for values of r.

  7. Computation

  8. Conceptual / Computational Formulas

  9. Computation / Conceptual Formula

  10. Conceptual Formula

  11. Computation / Computational Formula

  12. Computational Formula

  13. Problems Effecting the Interpretation • Non Linear Relationship

  14. Problems Effecting the Interpretation • Outliers

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