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I have chosen to compare the weights with the three factors listed above: age, gender and height and throughout this investigation I am aiming to show that weight of a certain group of people

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Introduction

Renee Uba

Data Handling Project

In this piece of coursework I am investigating how the weight of a sample of pupils can be affected by various factors e.g. age, gender, height etc.

        I have chosen to compare the weights with the three factors listed above: age, gender and height and throughout this investigation I am aiming to show that weight of a certain group of people may be affected by certain factors and that other factors may have no affect on the weight at all.

Plan:

        I have been given a survey on all the pupils in ‘Mayfield School’. I have over 800 cells of data containing the following information on a pupil:

  • Year Group
  • Surname
  • Forename
  • Age (in years and months)
  • Gender
  • IQ
  • Height (m)
  • Weight (kg)

In order to carry out my investigation I need to take a sample out of the collected information.

...read more.

Middle

My data is going to be collected in a frequency table and this information is diagrammatically going to be represented using:

  • Scatter diagrams – by drawing the line of best fit I will be able to determine how the two variables I am comparing relate to each other or not.
  • Box and Whisker plot (where my information is going to be obtained from doing a stem and leaf diagram and manually counting the data to achieve the median, lower quartile, upper quartile and interquartile range.  The median is useful as it helps me to find where the middle of the distribution lies and the box and whisker plot depicts one common measure of central tendency – the median and one measure of spread – Inter Quartile Range. The length from the maximum and minimum value indicates how symmetrical the data are. When the median lies far from the centre of the box or if one whisker is much longer than the other, I will know that the distribution is distorted to some extent.
  • Cumulative Frequency curves
...read more.

Conclusion

The data that has been entered may have been entered incorrectly or hurriedly and therefore resulting in anomalies that will affect my results when comparing the data. If I come across data that is erroneous I shall annul it from my sample because by collecting 60 data points for each gender I will have a large enough sample and taking ONE point out would not have a big difference on the end results.

Hypothesis:

  • I predict that a sample of year 11 girls will have a greater range of weight than girls in year 7.
  • I predict that girls in year 8 will weight more than boys in the same year (8).
  • I predict that the as the height increases so does the weight.; I will find a positive correlation between the height and weight.

...read more.

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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