Kah Leong, Yi Meng, Daven

We are supposed to conduct an experiment to take a video of a person walking at a constant acceleration of 0.5 m/s^2 for 5 seconds. 

For this, we started off at a original length of 0.500m, afterwards we increased the interval by 0.500m. By traveling the new marked distance in 1 second, we will be able to get the acceleration of 0.5m/s^2.

Our setup:

 

We expect our displacement time graph to be a curved line as we cover more distance within the same period of time (1 second)

Displacement-time graph:

From our s-t graph, our acceleration is 0.54ms^-2.

For the acceleration time graph, it was really hard to see the best fit line as the points are relatively packed together, thus we zoomed in and changed the y axis to 0.00-1.00 and we found out that our acceleration is around 0.375 m/s^2.

Acceleration-time graph

From the graph, the Tracker software uses the formula V=u+at to form this graph, but presents it in the form of v=at +b. Therefore, we know that our value of acceleration will be the value of "a" that is give in Tracker, which is 0.5560 ms^-2.

Since data is lost when tracker converts the graph from st to tv and finally to at (by comparing them with the previous points) , the most reliable acceleration value will be from our st graph. Therefore, our acceleration that we got in this activity is 0.54 ms^-2.

Why is it not a constant acceleration and not 0.5m/s^2?

It is very difficult to ensure that the acceleration is the same between each step. Also, instead of maintaining a constant rate of acceleration, we only increased our speed at different moments or intervals, hence the acceleration was not constant. This might also result in a difference in the distance covered within one second when compared to our proposed length. 

Secondly, another source of error will be that It is almost impossible for us to reach our marked interval at exactly 1.00 seconds. We might reach the marking slightly early or slightly later and this might affect the best fit lines of both graphs. 

As for the assumptions, we assume that all our movement  will be accurately tracked by the software.

the area covered by our hair in the video is relatively large. The software can track any point of the hair as it will still be the same as  the mass point that we have identified. This might result in a difference in the distance covered within one second when compared to our proposed length.