# I am conducting an experiment to show the relationship between the rate of reaction when catching a ruler under normal circums

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Introduction

My Data handling coursework

I am conducting an experiment to show the relationship between the rate of reaction when catching a ruler under normal circumstances (a quiet distraction free room) and those when under the influence of a distraction (Music from a CD player).

I will do this by dropping a ruler from a fixed and constant height from the test subject’s hand, and measuring the length (in cm) that it takes them to grasp the ruler as it is falling. Using a formula I can convert this into a time result. I will also repeat this when a distraction of music is being played, and observe whether or not there is a difference between the results.

Using this data, from a stratified random sample across the school, I hope to be able to prove or disprove a set of hypothesis that I will make based on my own, justified, opinions of reaction abilities between males and females and with distraction or without a distraction.

For the first drop, where there is no distraction, it would evidently be sensible to do the test in an empty, quiet room, where there is no chance of interruption, giving the subject full concentration on their task. This should make the test as fair as possible

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Mean | Standard Deviation | |

Without Distraction | 0.22 | 0.0532 |

With Distraction | 0.25 | 0.0596 |

The standard deviation is a way of comparing 2 sets of data.

√∑(x-x)²

n

x – piece of data

x – mean of the set of data

n – number of pieces of data

∑ - ‘sum of’

Using this data I can begin to start working on the hypotheses. Firstly, I will create a scatter graph and work out the correlation coefficient to see if there is a link between the two sets of time data.

Hypothesis 1

Correlation

From this it is possible to see a weak positive correlation between the two sets of results. Looking at the correlation coefficient (a number between –1 and 1) which shows between 2 sets of data the size of the correlation: -

The correlation co-efficient is: 0.548655.

Normally for a good link to exist this number should be above 0.7 so we can see that there is not a great relationship between the two sets but that there is at least a small connection.

First of all I sorted the data. Then I drew up 2 cumulative frequency tables.

Distraction | ||

reaction time | Frequency | Cumulative Frequency |

0.00<t<0.05 | 0 | 0 |

0.05<t<0.10 | 0 | 0 |

0.10<t<0.15 | 1 | 1 |

0.15<t<0.20 | 13 | 14 |

0.20<t<0.25 | 41 | 55 |

0.25<t<0.30 | 25 | 80 |

0.30<t<0.35 | 12 | 92 |

0.35<t<0.40 | 4 | 96 |

0.40<t<0.45 | 4 | 100 |

No Distraction | ||

reaction time | Frequency | Cumulative frequency |

0.00<t<0.05 | 1 | 1 |

0.05<t<0.10 | 0 | 1 |

0.10<t<0.15 | 6 | 7 |

0.15<t<0.20 | 24 | 31 |

0.20<t<0.25 | 46 | 77 |

0.25<t<0.30 | 15 | 92 |

0.30<t<0.35 | 6 | 98 |

0.35<t<0.40 | 2 | 100 |

0.40<t<0.45 | 0 | 100 |

From these I then constructed a cumulative frequency graph.

From the cumulative frequency diagram I can see that the non-distraction times are quicker as the have more of a steep curve. The times with Distraction have not got as steep a curve, which shows that the reaction times are not as fast as those which haven’t been distracted.

No distraction | Distraction | |||

Mean | 0.22 | Mean | 0.25 | |

Median | 0.22 | Median | 0.24 | |

Mode | 0.2 | Mode | 0.244949 | |

Minimum | 0.04 | Minimum | 0.13 | |

Max | 0.36 | Max | 0.42 | |

Range | 0.32 | Range | 0.29 | |

STDV | 0.053224 | STDV | 0.0596 |

Conclusion

spread is fairly consistent, though they have higher results, and the majority results are at the beginning.

I have found out that females are better at multi tasking than males. This is true because the mean for the females is lower than the males; the median is lower for the females. This shows that the results are more consistent, therefore making them better at multi tasking than men.

The frequency polygon shows that the female spread is more consistent than the males, as the males has a fluctuation in the middle, whereas the female results are fairly consistent throughout.

From the histogram I can tell that the females’ differences are spread more evenly than the males, as the males’ differences are concentrated in the middle area.

These factors prove that females are better at multi tasking than males.

The Overall Conclusion.

My first hypothesis was that I thought Reaction times would be faster without a distraction. I have used a cumulative frequency graph, a scatter graph, the mean, median, mode, the minimum and maximum results, standard deviation and correlation co-efficient to successfully prove my hypothesis correct.

My second hypothesis was that I thought that the difference between the two sets of results, being distracted or not, will be lower for the girls and higher for the boys. I used the mean, median, mode, minimum and maximum results, a Histogram and Frequency Polygons to successfully prove that females are better at multi tasking.

This student written piece of work is one of many that can be found in our GCSE Height and Weight of Pupils and other Mayfield High School investigations section.

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