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

stopping distance

Extracts from this document...


5 Stopping distances


1. Through the use Chart Wizard on Microsoft Excel, I have generated the following graphs:



Already, we see that thinking distance is a linear function. From 32km/hr onwards, every time speed increases by 16km/hr, the distance travelled by the woman before braking increases by a constant 3m.

The additional braking distance however, shares a nonlinear relationship with speed. With increasing speed, the braking distance travelled appears to increase at an even faster rate. The gradient of the curve becomes steeper and steeper, in contrast to the first line, where the constant slope gives it its linearity.  

...read more.


x1 = 32

x2 = 48

y1 = 6

y2 = 9

Gradient = y 2 – y 1  


x 2 – x 1

= (9-6)


= 3  (or 0.1875)


3) So far, we have y = 0.1875x + c. To find the constant, we can plug in the coordinate (48,9) for x and y.

9 = (0.1875)(48) + c

9 = 9 + c

c = 0

4) The final function for speed versus thinking distance looks like this:

f(x) = (3/16)x + 0

When graphing the linear function and finding its equation through the “trendline” option on Excel, I initially obtained y = 3x + 3.

...read more.


y value (3). Excel considers the x-axis as ordinal instead of numerical. It ignores the fact that when speed is 0km/hr, thinking distance is naturally 0m (the line should pass through the origin but it does not).

Of course, this mistake could have been easily avoided on my part. Had I chosen a “scatter” instead of “line” graph, the numbers on the x-axis would have progressed by their true value of 16km/hr instead of 1km/hr. The instant “chart type” was changed to “scatter”, the trendline showed the correct equation of

y = 0.1875x.

...read more.

This student written piece of work is one of many that can be found in our International Baccalaureate Maths 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 International Baccalaureate Maths essays

  1. Stopping distances portfolio. In this task, we may develop individual functions that model the ...

    Quadratic Relationship y = ax2 + bx + c The software calculates for the quadratic relationship: y = 0.0061x2 + 0.1643x + 0.6003 Speed [km/h] Overall stopping distance [m] Quadratic relation 32 12 12.1043 48 23 22.5411 64 36 36.1011 80 53 52.7843 96 73 72.5907 112 96 95.5203 Description

  2. portfolio Braking distance of cars

    Speed (km/h) Thinking distance (m) 32 6 48 9 64 12 80 15 96 18 112 21 x = speed y = thinking distance y = ax + b 6 = 32a + 0 32a = 6 a = y = x + b The value of b should be

  1. Portfolio Type II: Stopping Distances

    Speed (kmh-1) Overall Distance (m) 32 12 48 23 64 36 80 53 96 73 112 96 Figure 3 Figure 3 is a graph representing the relationship between speed and the overall stopping distance. This again is a quadratic curve and the best fitting equation (found using a GDC)

  2. Body Mass Index

    A positive phase shift will mean the graph moves to the right while a negative phase shift means the graph moves to the left. The maximum points of y=sin x are at 2n? + ?�2. So I'll try to locate that point on the data.

  1. The speed of Ada and Fay

    Furthermore, I also set Ada's velocity as "u m/s" and Fay's velocity is "v m/s". Ada is running in a straight line along the harbor path using the velocity of 6 m/s and Fay is using 8m/s running towards Ada, which its direction will change due to Ada's position.

  2. Interdisciplinary Unit

    Then I calculated and displayed the mean, median, mode, range and standard deviation for each set of class data. MEAN is one of the more common statistics. And it's easy to compute. All you have to do is add up all the values in a set of data and then

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