8.2.12

Correlations & Causes

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Factors Affecting Cancer

Both genetic and environmental factors can increase the likelihood of developing cancer. These factors are correlated with cancer but they are not causes.

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Environmental factors

  • Environmental factors that are associated with an increase in cancer include:
    • Exposure to radiation.
    • Smoking.
    • Alcohol consumption.
    • Eating a diet high in fat.
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Genetic factors

  • Genetic factors that are associated with an increase in cancer include:
    • Having certain alleles.
      • E.g. The BRCA1 allele can increase the chance of developing breast cancer.
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Correlation vs cause

  • Environmental and genetic factors have been found to correlate with cancer.
  • Correlations mean that there is an association between the two factors.
  • Correlations are different from causes because they do not always mean a person will develop cancer.
    • E.g. If a person smokes, they have a higher chance of developing cancer than a non-smoker but this does not mean they will definitely develop cancer.

Interpreting Correlations

Studies have found correlations between some environmental and genetic factors and the occurrence of certain cancers. It is important to be able to interpret data about correlations.

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Correlation

  • A correlation is a type of relationship between two different variables.
  • Correlations can be positive or negative. Sometimes data will show no correlation.
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Positive correlation

  • A positive correlation would look like this.
  • Two variables positively correlate, so when one variable increases so does the other variable.
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Negative correlation

  • Negative correlation looks like this.
  • When one variable increases, the other variable decreases.
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No correlation

  • No correlation looks like this.
  • There is no positive or negative correlation between the two variables.
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Causation

  • Correlation is not the same as causation.
  • Causation is where one variable is the cause of the other. Just because two variables correlate, this does not mean there is a causal relationship.
  • For example, in a hypothetical study, one might find that height positively correlates with having more children. This does not mean that being taller causes a person to have more children.
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Conclusions

  • Correlations do not necessarily mean causation.
  • Other factors need to be taken into consideration when interpreting graphs. E.g. -
    • Age.
    • Other aspects of variation in lifestyle (e.g. amount of exercise).
    • Sample size.
    • Gender.
    • Changes in healthcare provision.

Jump to other topics

1Biological Molecules

2Cells

3Substance Exchange

4Genetic Information & Variation

5Energy Transfers (A2 only)

6Responding to Change (A2 only)

7Genetics & Ecosystems (A2 only)

8The Control of Gene Expression (A2 only)

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