Correlational Analysis and Assessment

Correlational Analysis

• Focus on correlational analysis for assessment three.
• Involves examining the strength and direction of the relationship between two continuous variables.

Pearson Correlation

• The Pearson correlation coefficient is denoted as r.
• r ranges from -1 to +1.
  • -1: Perfect negative linear relationship (as one variable increases, the other decreases).
  • 0: No relationship between variables.
  • +1: Perfect positive linear relationship (as one variable increases, the other increases).

Assumptions of Correlational Analysis

• Variables should be measured on a continuous scale.
  • Use numerical values, not categorical variables.
• The relationship being tested should be linear.
  • Expect a straight-line pattern.
• Both variables should be approximately normally distributed.
  • Values spread out in a bell-curve pattern.
• No extreme outliers, as they can skew results.

Addressing Violated Assumptions for Pearson Correlation

• Acknowledge the issue in the results and discussion sections.
• No need to explain basic concepts (outliers, normality, linearity).

Interpreting Correlation Coefficients in SPSS

• Correlation coefficients (r values) are marked for statistical significance.
  • Single asterisk: Significant at the 0.05 level.
  • Double asterisk: Significant at the 0.01 level.
• Interpret the direction of the effect.
  • Positive r: Positive relationship (both variables increase together).
  • Negative r: Negative relationship (as one variable increases, the other decreases).

Strength of Relationship

• Use Cohen's guidelines:
  • r around 0.1: Small effect.
  • r around 0.3: Medium effect.
  • r around 0.5 and above: Large effect.

Assessment Three: Correlation Analyses

• Conduct two separate correlation analyses.
  • Personality trait and outcome variable.
  • Second personality trait or continuous demographic variable (e.g., age) and outcome.

Interpreting Results Examples

• Is the relationship between fatigue and sleep quality statistically significant?
• What is the direction of the effect in this particular example?

Structure of the Results Section

• Provide descriptive statistics for each variable (mean and standard deviation).
• Comment on missing data or outliers.
• Comment on the assumption check.
• Present results of both Pearson correlations (r value, significance level, direction, strength).
• Include two figures (scatter plots).
• Adhere to APA seventh style.

Structure of the Discussion Section

• Summarize research question and hypothesis briefly.
• Compare results to prior research, noting discrepancies or similarities.
• Discuss the implications for future research.
• State strengths and limitations.
• Provide a clear conclusion.