• Join over 1.2 million students every month
  • Accelerate your learning by 29%
  • Unlimited access from just £6.99 per month

What factors made a person better at estimating the size of an angle or the length of a line.

Extracts from this document...

Introduction

Michael Mitchell        Statistics Coursework        Mrs Williams

From this data we made a hypothesis on what factors made a person better at estimating the size of an angle or the length of a line. My hypothesis was that year 10 pupils would be better at estimating both the size of angles and the length of lines than the adults and the year 7 children but adults answers will be closer to the mean on average. To prove this I would have to use the information in the spreadsheet .

I first found the mean of angle 1 ,angle2 ,line 1 and line 2 in all of the sample of year ten all of the sample of year seven and all of the sample of the adults because using this I could find the average percentage error of each group because I felt this was essential in trying to prove the hypothesis I made earlier .The means for each were as displayed in the table below:

Year 10

Year 7

Adults

Angle1

57.76

65.42

51.25

Angle 2

142.72

141.04

147.05

Line 1

3.87

4.55

3.6275

Line 2

14.52

14.61

12.7325

At the moment when I produced

...read more.

Middle

Year 7

Upper Fence

Lower fence

Angle 1

92.5

32.5

Angle 2

205

85

Line 1

7.25

1.25

Line 2

19.5

7.5

And for the adults

Adults

Upper Fence

Lower fence

Angle 1

65

33

Angle 2

188.75

110.75

Line 1

5.5

1.625

Line 2

6.875

17.675

With this data we deleted rogue values which amounted only to three.

So now we can find the percentage error without worrying about rogue values influencing what could be a vital difference.

Year 10 (%)

Year 7 (%)

Adults (%)

Angle 1

7.2

18.9

6.8

Angle 2

7.9

9.03

5.12

Line 1

4.6

23

2

Line 2

16.17

16.88

1.9

This gives us an idea of to which group is better at estimating the sizes of angles and the lengths of lines but to see this in another way we can use box plots which are very useful for comparing sets of data from different groups within a certain population. The length of the whiskers

...read more.

Conclusion

If I could reiterate the experiment I would make a more detailed hypothesis inducing me to analyse all possible fields that could of affected a persons ability to estimate the size of angles and lengths of lines an example of this is gender or intelligence but the field that I investigated which was age came out to me with a very clear result , this was that on average the older you are the better you are at estimating the size of an angle and the length of a line ,but we must take into account that we used a random sample of 25% from each group this meant that we could of missed some peoples estimates that could of affected or swayed the results to a different conclusion this could be important. This means  the concluding statement may not actually be correct if further investigated with more detail and with more age groups such as year 8 , 9 and 11 but is still correct for the investigation we carried out.

...read more.

This student written piece of work is one of many that can be found in our AS and A Level Probability & Statistics section.

Found what you're looking for?

  • Start learning 29% faster today
  • 150,000+ documents available
  • Just £6.99 a month

Not the one? Search for your essay title...
  • Join over 1.2 million students every month
  • Accelerate your learning by 29%
  • Unlimited access from just £6.99 per month

See related essaysSee related essays

Related AS and A Level Probability & Statistics essays

  1. The mathematical genii apply their Statistical Wizardry to Basketball

    For Lee the expected mean value would be E[X] = = 3.3625 (4 d.p.) For Dom the expected mean value would be E[Y] = (4 d.p.) These results demonstrate the average amount of shots it takes until the performer scores.

  2. Statistics - Men are more accurate than women at estimating the length of a ...

    The mean is the average number and with this I can see which figure from both sets of results is closest to the actual length and size. This will show me whether my two hypotheses are correct or not. Length of line Men's Mean: 2550 / 30 = 8.5cm Women's

  1. Statistics. The purpose of this coursework is to investigate the comparative relationships between the ...

    The line of best fit intercepts y axis through at 19310. This does not make sense: if a car has not been driven, this anomalous result of 19310 miles is invalid. Weak correlation is also down to other factors: if clients have bought a car which is brand new, they

  2. Design an investigation to see if there is a significant relationship between the number ...

    and working away from it, I am ensuring that I am working in the safest conditions possible. I have opted to use a belt transect that runs up the shore as opposed to across the shore. Placing the transect across the shore poses dangers, as the transect would inevitably incorporate deep gullies, that can reach up to 10ft deep.

  1. Guestimate - Is there a link between a person's ability to estimate the length ...

    An example of the way we used this can be seen on page 17, this was to make it easier to interpret our results.

  2. Guestimate - investigate how well people estimate the length of lines and the size ...

    of students from set Number in year However, if I had been using systematic random sampling I would have used the following method to find out the gap between my choices: Number in year = every Xth student Sample size Then I would role a dice to find a starting number so I avoid being biased by picking it myself.

  1. "The lengths of lines are easier to guess than angles. Also, that year 11's ...

    So, the numbers I am going to use are: 91, 98, 106, 113, 3, 10, 17, 24, 31, 38, 45, 52, 59, 66, 73, 80, 87, 94, 101, 108, 115, 5, 12, 19, 26, 33, 40 Year 11 Random Number Generator 127 was the number the generator produced, so I

  2. Identifying Relationships -Introduction to Statistical Inference.

    (2-sided) Pearson Chi-Square 10.717 3 .013 Likelihood Ratio 11.274 3 .010 Linear-by-Linear Association 2.615 1 .106 N of Valid Cases 85 Making a decision: In effect the null hypothesis is presumed innocent until proven guilty We require a decision rule to help us to test the hypothesis we have

  • Over 160,000 pieces
    of student written work
  • Annotated by
    experienced teachers
  • Ideas and feedback to
    improve your own work