# Spearman’s Rank Correlation Coefficient

## Presentation on theme: "Spearman’s Rank Correlation Coefficient"— Presentation transcript:

Spearman’s Rank Correlation Coefficient
Pages 28 to34

Key Terms associated with Correlation
Spearman’s Rank Correlation Coefficient A statistical measure which shows the strength of a relationship between two variables. It also outlines the type of relationship whether positive or negative. Minimum of 10 sets of paired values needed for this test to be statistically reliable. A strong correlation indicates that there is a link between the two factors but not that one causes the other. For example there may be a strong correlation between the incidence of sunburn and the sale of ice cream, but this does not imply that ice cream causes sunburn. This test simply indicates that there may be a causative link which can be explored with further investigation. Either write a definition or draw a diagram to illustrate the terms below (see page 28 & 29). Correlation Scatter graphs Independent variable Line of best fit Dependent variable Residual value Positive linear relationship Negative linear relationship

Spearman’s Rank Write out the formula for the calculation of r
Interpretation of r s Increasing Increasing Significance Significance Perfect No Perfect Negative Correlation Positive Linear Linear Relationship Relationship How do we know if an answer is close enough to 1 to be considered significant?

Questions - Page Explain why 95% is a cut off point for significance. How do you calculate degrees of freedom? What do significance levels of 95%, 99% and 99.9% mean? Carefully study the worked example on page 30 & 31.