Research Question- How does time affect the position of the buggy?
Independent variable- Time (seconds)
Dependent variable- Position (meters)
Controls- Surface where the buggy is traveling, type of buggy
We used the track for every trial of our experiment, and we had the same buggy throughout
Procedure for Video Analysis
Procedure for Motion Sensor
Procedure for Stopwatch
Independent variable- Time (seconds)
Dependent variable- Position (meters)
Controls- Surface where the buggy is traveling, type of buggy
We used the track for every trial of our experiment, and we had the same buggy throughout
Procedure for Video Analysis
- Set up the camera so it can see the buggy and the entire track which measures 2.275m
- Make sure the camera will stay still throughout the video
- Start the buggy and let it travel from left to right
- Import the video to LoggerPro and run a video analysis to create a position vs. time graph
Procedure for Motion Sensor
- Connect the motion sensor to LoggerPro on a computer
- Place the motion sensor at the end of the track
- Start the buggy in the air and then set it down as the motion sensor starts
- Stop data collection and analyze position vs. time graph
Procedure for Stopwatch
- Start the buggy in the air and then set it down
- Start the timer and let it run for 5 seconds
- At the 5 second mark, stop the buggy and record the position
- Repeat 3 times for each set time
- Repeat steps and continue to decrease time by 0.5 seconds until you reach 0.5 s as the final measurement
- Create a plot of position vs. time graph
Recorded Raw Data for Stopwatch
(Video Analysis and Motion Sensor Data in LoggerPro)
(Video Analysis and Motion Sensor Data in LoggerPro)
Motion Sensor Graph
Position = -0.4193 m/s * Time + 2.071 m
Slope- As time increases by 1 second, the buggy's position decreases by 0.4193 m
Y-Intercept- The buggy started 2.071 m away from the motion sensor (should have been 2.275 m because that is how long the track is)
Slope- As time increases by 1 second, the buggy's position decreases by 0.4193 m
Y-Intercept- The buggy started 2.071 m away from the motion sensor (should have been 2.275 m because that is how long the track is)
Video Analysis Graph
Position = 0.4277 m/s * Time - 0.1300 m
Slope- As time increases by 1 second, the buggy's position increases by 0.4277 m
Y-Intercept- The buggy's initial position was -0.1300 m (should have been 0 m)
Slope- As time increases by 1 second, the buggy's position increases by 0.4277 m
Y-Intercept- The buggy's initial position was -0.1300 m (should have been 0 m)
Stopwatch Graph
Position = 0.4116 m/s * Time + 0.1700 m
Slope- As time increases by 1 second, the buggy's position increases by 0.4116 m
Y-Intercept- The buggy's initial position was 0.1700 m (should have been 0 m)
Uncertainty bars come from the averages
Conclusion- The motion lab 3 ways was designed to compare and contrast the effectiveness of using a stopwatch, motion sensor, and video analysis to analyze the change in position of a buggy over time. Based on our results, the three methods produced comparable slopes for the position vs. time graph, describing the velocity of the buggy. We should have placed the motion sensor on the left side of the track instead of the right side, which explains why the slope is negative, but the magnitude of the three slopes (0.4193, 0.4277, 0.4116) is very similar. In addition, the y-intercept for the motion sensor graph was affected by our placement. Since the track was 2.275 m long and the motion sensor was placed at the end of it, the y-intercept should have been 2.275 and it should have been 0 for the other two graphs. After analyzing our evidence, it is clear that all three approaches work to find the velocity of our buggy. This can be generalized to show that the method of measurement doesn't matter, what is important is taking accurate position vs. time measurements and then calculating the slope of the graph. This knowledge will help in the rest of the class because we can use the most efficient method to measure motion since we know that it will end up with similar results to the other methods.
Evaluating Procedures- One source of uncertainty in our stopwatch data was reaction time because Alina had to watch her stopwatch and react at the right time to stop the buggy at each of our time markers. Although she was pretty successful, it is impossible to do this perfectly by stopping the cart at exactly 1.5 seconds for example. Another source of uncertainty was the conversion from pixels to meters in the video analysis. This process has a level of uncertainty associated with it because I provided the conversion that the length of the track was 2.275 m, but it can't be converted perfectly.
Improving the Investigation- One way to improve the investigation would have been to combine two of the tracks or have more space for the buggy to run because it was difficult to create a large enough range of data with our track that measured 2.275 m. Instead of starting the buggy before the meter stick like the directions stated, we had to turn the buggy on in the air and start the timer when we placed it down to ensure that we would have enough room for our 5 second trial. Our investigation also would have been better if we had placed the motion sensor on the left side of the track because then all of our graphs would have had positive slopes and y-intercepts around 0. Finally, if there was a way to set the buggy to run for a certain amount of time instead of having to stop it after that interval, this would reduce the uncertainty of reaction time in the experiment.
Slope- As time increases by 1 second, the buggy's position increases by 0.4116 m
Y-Intercept- The buggy's initial position was 0.1700 m (should have been 0 m)
Uncertainty bars come from the averages
Conclusion- The motion lab 3 ways was designed to compare and contrast the effectiveness of using a stopwatch, motion sensor, and video analysis to analyze the change in position of a buggy over time. Based on our results, the three methods produced comparable slopes for the position vs. time graph, describing the velocity of the buggy. We should have placed the motion sensor on the left side of the track instead of the right side, which explains why the slope is negative, but the magnitude of the three slopes (0.4193, 0.4277, 0.4116) is very similar. In addition, the y-intercept for the motion sensor graph was affected by our placement. Since the track was 2.275 m long and the motion sensor was placed at the end of it, the y-intercept should have been 2.275 and it should have been 0 for the other two graphs. After analyzing our evidence, it is clear that all three approaches work to find the velocity of our buggy. This can be generalized to show that the method of measurement doesn't matter, what is important is taking accurate position vs. time measurements and then calculating the slope of the graph. This knowledge will help in the rest of the class because we can use the most efficient method to measure motion since we know that it will end up with similar results to the other methods.
Evaluating Procedures- One source of uncertainty in our stopwatch data was reaction time because Alina had to watch her stopwatch and react at the right time to stop the buggy at each of our time markers. Although she was pretty successful, it is impossible to do this perfectly by stopping the cart at exactly 1.5 seconds for example. Another source of uncertainty was the conversion from pixels to meters in the video analysis. This process has a level of uncertainty associated with it because I provided the conversion that the length of the track was 2.275 m, but it can't be converted perfectly.
Improving the Investigation- One way to improve the investigation would have been to combine two of the tracks or have more space for the buggy to run because it was difficult to create a large enough range of data with our track that measured 2.275 m. Instead of starting the buggy before the meter stick like the directions stated, we had to turn the buggy on in the air and start the timer when we placed it down to ensure that we would have enough room for our 5 second trial. Our investigation also would have been better if we had placed the motion sensor on the left side of the track because then all of our graphs would have had positive slopes and y-intercepts around 0. Finally, if there was a way to set the buggy to run for a certain amount of time instead of having to stop it after that interval, this would reduce the uncertainty of reaction time in the experiment.