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Guestimate - investigate how well people estimate the length of lines and the size of angles.
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The results we found for our class were as follows:ItemAverageestimateCalculationAveragepercentageerrorAngle one Acute This difference suggests that there is something worth investigating further. The data we had already collected however was not sufficient to draw a firm conclusion from, as it was only our age group and in the top set. We widened our search for data and asked the whole of year ten, the whole of year seven and some adults working at our school.
We asked each person taking part to specify their age group, year 7, year 10 or adult their gender, male or female and their maths set, This wider availability of data would enable us to draw a firmer conclusion and create more hypotheses to investigate and prove either correct or incorrect. Once the data had been collected from year seven, year ten and 68 adults the data was entered onto a computer database, in Microsoft Excel. An example of the way we used this can be seen on page 17, this was to make it easier to interpret our results.
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We used our calculator on the random number generator to randomly select the people not stratifying in accordance to gender or set. We then looked at whether they stood out to be better at estimating lines or angles.
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This bar chart shows that our year 10 top set was quite typical of the whole of year 10, although as the fact it is a top set would indicate it shows they are slightly better. This will then tell me which one that people were nearest to. On the next page is an example of the table I used to work out the cumulative frequencies and also the cumulative frequency graph I drew. Line 2 only has 43 people as two were obvious outliers. These results back up what our bar charts of percentage errors tell us.
That people were better at estimating shorter lines and larger angles.
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