# maths estimation coursework

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Introduction

Section B

In this section of my assignment, I will carry out my own investigation on estimation similar to the previous investigations I have analysed. Although in this investigation I will improve upon the previous investigations, taking what they left out from their investigations and including it in my own.

I am doing this investigation as the previous investigations had some missing information, and some did not have representative samples, my investigation will be representative of the estimating population and will have more reliable data to ensure that more conclusions can be drawn from the estimations given.

The secondary data from the previous investigations seemed to suggest that there may be a link between estimation and gender, particularly David, Mary and John’s results, I will see if this is the case in my own investigation, while also taking age into consideration at the same time. Also, Michael’s data showed a correlation between estimation of angle and estimation of length. I will explore this also in my investigation.

The estimating population shall be comprised of Year 8’s and Year 12’s from our school.

Middle

I will now calculate my stratified sample for 140 results.

Remembering my populations of year 8 and year 12:

Year 8:

Female - 53

Male - 58

Overall - 111

Year 12 population:

Female - 65

Male - 50

Overall - 115

Total population: 226

Firstly, for a stratified sample I will need to calculate haw many year 8s and year 12s I will need.

Year 8

Year 12

From my calculations I have determined that I will require:

69 Year 8 and 71 Year 12

I now need to calculate how many of each gender group I will have need in order to obtain a representative stratified sample

Not forgetting the gender ratio of year 8: 58 males to 53 females

Year 8 Males: 58 / 111 x 69 = 36

Year 8 Females: 53 / 111 x 69 = 33

Or the gender ratio of year 12: 50 males to 65 females

Year 12 Males: 50 / 115 x 71 = 31

Year 12 Females: 65 / 115 x 71 = 40

Both year groups add up to 69 and 71, so my sample of the population amounts to 140 people. I have now determined that this is a representative stratified sample and I will proceed to use at least 140 people in my sample for my investigation.

Many factors need to be considered when choosing a suitable area of estimation to investigate. I believe that the main one is that of time consumption, how long these results will take to collect.

Conclusion

It is possible that in my second hypothesis that the gender distribution of each estimating group could have manipulated or distorted the results. By investigating the effect of gender on estimation, I will be investigating a new hypothesis, and simultaneously adding to my second.

My third Hypothesis is that year 12 girls will be better estimators than year 12 boys. To investigate this I will display the percentage error of each gender of each year group in a scatter graph

.

With the exception of 3 out lying results for females in year 12, they show a great correlation of estimation of angle to estimation of length. Their mean percentage errors are:

Length: 12.59

Angle: 4.16

And the males are:

Length 13.94

Angle 4.28

On both accounts the girls are shown to be better estimators. This would suggest to me that girls are better estimators and that my third hypothesis h\s been proven.

My conclusion is that there is no correlation between estimation of length and angle. That age has a direct correlation with estimation, and that gender has a correlation to estimation in that girls are better estimators than boys.

If I were to do this experiment again…

Do r squared correlation thingfor 1,2,3

Do more Calculations for 2 and 3

Do better conclusion and compare to section A

Do recommendations for future experiment

Change wording

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