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Relationship between Variables
Assessment Statement1.1.6 Explain that the existence of a
correlation does not establish that there is a causal relationship between two variables.(3).
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Correlation
• Typically in IB Biology your experiment may involve a continuous quantitative independent variable and a continuous quanitative variable dependent variable. – e.g effect of enzyme concentration on the rate of
an enzyme catalysed reaction.• The statistical analysis would set out to test
the strength of the relationship (correlation).
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EXAMPLES OF CORRELATION
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CALCULATING CORRELATIONS ON EXCEL
• There are two tests for correlation:1. the Pearson correlation coefficient ( r ), used from
normal distribution data
2. and Spearman's rank-order correlation coefficient ( r s ) used from non-normal distribution data
• These both vary from – +1 (perfect correlation) through – 0 (no correlation) – to –1 (perfect negative correlation).
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Correlations & Relationships between variable
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Correlation does NOT mean Causation
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Interpreting R - Values
• Exactly –1. A perfect downhill (negative) linear relationship
• –0.70. A strong downhill (negative) linear relationship• –0.50. A moderate downhill (negative) relationship• –0.30. A weak downhill (negative) linear relationship• 0. No linear relationship• +0.30. A weak uphill (positive) linear relationship• +0.50. A moderate uphill (positive) relationship• +0.70. A strong uphill (positive) linear relationship• Exactly +1. A perfect uphill (positive) linear relationship
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Correlation does NOT mean Causation
• It is important to realize that if the statistical analysis of data indicates a correlation between the independent and dependent variable this does not prove any causation. Only further investigation will reveal the causal effect between the two variables.
• Correlation does NOT imply causation. Here are some unusual examples of correlation but not causation's !– Ice cream sales and the number of shark attacks on swimmers are correlated. – Skirt lengths and stock prices are highly correlated (as stock prices go up, skirt
lengths get shorter). – The number of cavities in elementary school children and vocabulary size have a
strong positive correlation. • Clearly there is no real interaction between the factors involved simply a
co-incidence of the data.• Once a correlation between two factors has been established from
experimental data it would be necessary to advance the research to determine what the causal relationship might be.
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