Tally Chart for men estimating the length of the line.
Tally Chart for women estimating the length of the line.
Tally Chart for men estimating the size of the angle.
Tally Chart for women estimating the size of the angle.
From looking at my results at first glance I noticed that men are better at estimating the length of the line, but the angle results are very similar from both genders. Now I have my results from 30 men and 30 women, I am going to draw up some cumulative frequency tables so I can work out the mean number. By having the mean number it shows me which gender is better on average at estimating the size of my angle and the length of my line. The whole point of doing cumulative frequency charts is to work out the total and from that I can work out the mean (average) which will help me to see whether my two hypotheses are correct.
Men line
Women Line
Men angle
Women angle
By using the total from each cumulative frequency chart I can now work out the mean number by dividing the total by 30 as 30 is the number of each gender I asked to estimate the length of the line and the size of the angle. 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 Mean: 3140 / 30 = 10.4cm
Size Of Angle
Men’s Mean: 1310 / 30 = 43.6 degrees
Women’s Mean: 1395 / 30 = 46.5 degrees
From working out the mean for the men’s and women’s sets of data I found out that my two hypotheses are correct in saying that “Men are more accurate than women at estimating the length of a line” and “Men are more accurate than women at estimating the size of an angle”. As the actual size of the line on the paper is 9cm long and the size of the angle on the paper is 45 degrees.
As you can see the estimating from both genders was ever so close but my 2 hypotheses are correct.
Using the data from my cumulative frequency table I then drew up some cumulative frequency graphs, by doing this I can see the mid-interval value, upper quartile and lower quartile. (See pages 2, 3, 4 & 5)
I can now compare graphs to see if my hypotheses are correct which I’ve already found out that it is from working out the mean number from using the tally charts. Below show the mid-interval value, upper quartile and lower quartile from each graph.
Men line Women line
Mid-interval value = 80mm mid-interval value = 100mm
Upper quartile = 88mm Upper quartile = 109mm
Lower quartile = 72mm lower quartile = 91mm
Men angle Women angle
Mid-interval value = 42 degrees mid-interval value = 46 degrees
Upper quartile = 45 degrees upper quartile = 50 degrees
Lower quartile = 36 degrees lower quartile = 39 degrees
Now that I have the mid-interval value, upper quartile, and lower quartile I can draw up some box plots which will help me to see overall what my results show. E.g. positive skew.
(See pages 6 & 7)
Conclusion on next page
Conclusion
From my investigation on working out if my two hypotheses are correct or not, I have found out that they are both correct in saying that “Men are more accurate than women at estimating the length of a line” and “Men are more accurate than women at estimating the size of an angle”. But the size of the angle results compared against each gender are very close, I think if I had asked more people from each gender then I would have had better results, giving me a very different mean numbers. I don’t think they would have been as close.
On page 8 I have written an evaluation about my project with improvements I could have made to give me better results and what I thought about my overall project.
Coursework by Michael Biggar