📊

Understanding Pearson's r and Correlation

Mar 7, 2025

Lesson on Pearson's r and Correlation Coefficients

Introduction

  • Focus on Pearson's r, also known as the Pearson Product-Moment Correlation Coefficient.
  • Discusses the significance of relationships between two variables using Pearson's r.

Understanding Correlation Coefficients

  • Very Low Correlation: Less than ±0.30
  • Low Correlation: 0.30 to 0.50 (positive or negative)
  • Moderate Correlation: 0.50 to 0.70 (positive or negative)
  • High Correlation: 0.70 to 0.90 (positive or negative)
  • Very High Correlation: 0.90 to 1.00 (positive or negative)

Hypothesis Testing

  • Null Hypothesis: Generally states there is no significant relationship.
  • P-value: Key to deciding hypothesis outcome.
    • Accept the null hypothesis if the p-value is higher than the alpha level (commonly 0.05).
    • Reject the null hypothesis if the p-value is lower than the alpha level.

Example: Motivation Study

  • Variables: Additional grades, verbal praises, peer appreciation.
  • SOP (Standard Operating Procedures): Created to study factors affecting motivation.

Data Analysis Process

  1. Calculate Averages:

    • Use formulas to calculate averages for different responses (e.g., =AVERAGE for statements).
    • Repeat the averaging process for variables like verbal praises and peer appreciation.

  2. Using Pearson's r:

    • Access the Data tab to use Pearson's r analysis.
    • Input necessary values and check for labels.
    • Results output on a new worksheet.

Example Results

  • Average Non-verbal Process & Academic Grades:

    • r = -0.112
    • P-value = 0.975 (Not significant)
    • Accept the null hypothesis.

  • Peer Appreciation & Academic Grade:

    • r = 0.086
    • P-value = 0.651 (Not significant)
    • Accept the null hypothesis.

Conclusion

  • Results indicate non-significant correlation in tested examples.
  • Emphasizes importance of analyzing p-values to verify the significance of correlation.

Closing

  • Encourage audience to like, subscribe, and hit the bell icon for updates.
  • Invites viewers to join for the next video.

These notes capture the essence of Pearson's correlation coefficient analysis as discussed in the lecture video, with example applications to motivation factors and academic performance.

Full transcript