Correlation Flashcards
Correlation
_ ? _ Studies:
- Data are collected as they naturally exist
- No effort to manipulation of variables
Observational Studies:
- Data are collected as they naturally exist
- No effort to manipulation of variables
Correlation
_ ? _ Studies:
- Subset of observational studies
- Systematic investigation of relationships among 2 or more variables
- Predict the effect of one variable on another
Exploratory Research:
- Subset of observational studies
- Systematic investigation of relationships among 2 or more variables
- Predict the effect of one variable on another
Correlation
What kind of research?
- Describe
gray
Prospective Research =
- Longitudinal Studies
- Risk
- Prediction
Correlation
What kind of research?
- Describe
gray
Retrospective Research =
- Risk
Correlation
What kind of research?
- Describe
gray
“snap shot”
Cross-sectional Research =
Correlation
What kind of research?
- Describe
gray
Longitudinal Research =
Correlation
The strength of the relationship, values between –1.0 and +1.0:
- “0” = ?
- 1.0 = ?
- -1.0 = ?
The Correlation Coefficient
The strength of the relationship, values between –1.0 and +1.0.
- “0” is no relationship
- 1.0 = perfect positive relationship
- -1.0 = perfect negative relationship
Sign implies direction of the relationship.
Correlation
Assumptions for correlation = ?
- Scores represent the underlying population
- Scores are normally distributed
- Each subject has a score for both X and Y
- X and Y are independent measures
- The value of one data point does not depend on the value of the other
- Time is not a variable
- X and Y values are observed, not controlled
- Relationship between X and Y is linear, not curvilinear
Correlation
Correlations quantify strength of linear or curvilinear relationship?
Correlations quantify strength of linear relationship only.
Correlation
Interpretation of Strength of Correlations
- ≤ .25 = ?
- .25 to .50 = ?
- .50 to .75 = ?
- ≥ .75 = ?
Interpretation of Strength of Correlations
- ≤ .25 = Little or no relationship
- .25 to .50 = Low to fair
- .50 to .75 = Moderate to good
- ≥ .75 = Strong relationship
Correlation
What are the limitations of correlations?
- Relationship between TWO variables only
- Does not account for the effect of any other variable
- Only quantifies linear relationships
- Does not tell us “cause and effect”
- Does not account for agreement
- Highly influenced by the range of observations
- Average values suppress individual variation and can inflate r
Correlation
r =
r^2 =
r = Pearson Product-Moment Correlation Coefficient
r^2 = Coefficient of Determination
- The square of the correlation coefficient (r^2) is called the “coefficient of determination”
- More directly interpretable
- = “the percent of variance in y that is explained (or accounted for) by x”
Correlation
Conventional effect sizes for r:
- r = .10 = ?
- r = .30 = ?
- r = .50 = ?
Power and Effect Size for Correlation
- Correlation coefficient, r, is the effect size index for correlation
- Conventional effect sizes for r (notice that they are DIFFERENT from Cohen’s d, and eta squared…)
- r = .10 = small
- r = .30 = medium
- r = .50 = large
