Motion Detector/Video Analysis Lab + Write Up

1) Measurement of acceleration due to gravity from a motion detector.

Our acceleration due to gravity was 9.15m/s^2

Aside from the acceleration, we measured the velocity at which the ball fell, as well as the changing position. 

We measured it buy using the motion detector to try its position. We used the motion detector by mounting it around 5 feet high and pointing downward. We then dropped a ball from around 4 feet high directly below the motion detector. As the motion detector tracks the position, it loads the data into loggerpro which then tracks the velocity at which it fell based off its position. Loggerpro provides us with graphs to visualize the velocity and position, as well as providing the slope of each graph.

Our results were 1.4 meters for the position in which the ball fell, 1.145m/s for the velocity, and 9.15m/s^2 for the acceleration.

The standard deviation form my results was 0.05.

2) Measurement of acceleration due to gravity from video analysis

For this experiment, I dropped a ball similarly to the last, but did it on camera and tracked the position and velocity using Vernier Video Analysis. 

I measured these by first taking a video of me dropping a basketball from around 5 feet. I then uploaded the video onto Vernier Video Analysis, where I used the plot points feature. The plot points feature consists of the video being analyzed frame by frame, in which you plot a point on the ball every frame at which it is falling. Vernier will then provide a position and velocity graph based off the points. I also put a pool stick on the ground for measurement, in which it is also used for providing the right measurements.

My results were 1.1 meters being the position, 1.4m/s being the velocity, and 9.34m/s^2 being the acceleration. 

The standard deviation from my results was 0.38. 

3) Write up on measure variability      

The percent difference between both of the experiments was 2.06%, 9.15 and 9.34 being my two values.

My measurements do agree within the uncertainty determined from the standard deviation. My uncertainty for the Motion Detector experiment was 0.05 and my uncertainty for my Video Analysis experiment was 0.38. The uncertainty calculated between the two values was 0.43. From the Motion Detector experiment, a measurement that caused uncertainty was if the ball was in line with the motion detector. If it was off to the side and not in the preferred dropping line, that could cause the motion detector to not track the falling ball properly. From the video analysis, some measurements that cause for uncertainty were consistently plotting the same point on the ball and the frame rate disrupting accurate points. When using Vernier, it is suggested to plot the ball on the same part each frame. However, this can be hard to do as getting the point on the right pixel is not an easy task. The frame rate of the camera also effects this because you want to plot multiple points of the ball. If you are only plotting a few points, this can cause more uncertainty in the graphing, leading to inaccurate values being used. After using addition propagated uncertainty, my measurements still agree with my estimated uncertainty. I feel both are useful and can be a good way of finding the uncertainty; however, I think the using the standard deviation is more useful because you can directly use the other values that were in the process of getting your average. This way, I believe you can get a closer value to the others.