A **Scatter Graph** shows how two sets of data may be related. Note that, on a scatter graph, the points are not joined up.

The relationship between the two sets of data is known as the **Correlation**. There are three types of correlation:

If one value increases as the other also increases, then this is a **Positive Correlation**;

If one value falls as the other increases, then this is a **Negative Correlation**;

If there is no link between the two sets of data, then there is **No Correlation**

Note that an increase in one value does not necessarily *cause* the other value to change: for example, a good result in a Maths test does not cause a good result in a History test.

A teacher wanted to know whether the performance in a test was linked to the distance the student travelled to school. The teacher obtained the following results:

Distance (km) | Test Score |
---|---|

0.1 | 45 |

0.1 | 65 |

0.2 | 28 |

0.3 | 76 |

0.5 | 55 |

0.6 | 48 |

0.9 | 64 |

1.1 | 41 |

1.5 | 30 |

1.8 | 52 |

1.8 | 75 |

1.9 | 35 |

2.1 | 42 |

2.2 | 65 |

3.0 | 30 |

3.6 | 71 |

By plotting a scatter diagram, or otherwise, indicate the nature of the correlation between the distance the student lives from school, and the results in a test.

The plotted graph indicates there is no strong link between the two pieces of data.

Answer: No correlation

A survey examined the relationship between the amount of time spent revising for a test, and the results of a test. The information is shown on a scatter graph, below. What is the relationship between revision and test scores?

As the time spent revising increased, the test score increased.

Answer: Positive correlation

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