Buggy Lab

Grace Chung                                                                                                                                                               September 13, 2021

Partners: Emmy Xu and Jungwoo Park                                                                                                       Written: September 26, 2021

​

​

​

​

Problem: 

How does time affect the position of this remote control buggy? Is this relationship between time and position positive or negative and is it linear, quadratic, cubic, etc.? Define said relationship using a graph with a defined equation. 

​

Variables: 

The independent variable, or the variable that you actively change (also the x coordinates of the graph), is time measured in seconds (s). The dependent variable, the variable that changes as a result of the independent variable (the y coordinates of the graph), is the position of the buggy, from the initial position zero measured in centimeters (cm). There are several control variables or variables that must stay constant in order for the experiment to be successful. These variables include the use of the same buggy, which will control speed, mass, and air resistance. In addition, the direction of the buggy, the track of where the buggy goes, and the starting point of the car must all be the same in order to maintain consistency. 

​

Developed Method:

In order to gather accurate data, we found a smooth track in the hallway and found a marked ridge of the ground to be the starting point. We had one person release the buggy, one person time the buggy, and one person catch the buggy. The timer began when the back wheels of the buggy hit the We then marked down where the buggy stopped using post-it notes and continued onto the next trial. We had 6 positive time trials and 5 negative ones. We repeat the same time trial twice in the positive direction, but only once in the negative direction because of time. We used several meter sticks in order to get an accurate measurement. We recorded the data afterward. 

​

Procedure:

First, we drop the car several meters away from the starting point and start the stopwatch

as soon as the back wheels hit the starting point, or the origin zero. We stop the car when

the timer runs out, and mark it with a post-it note. We repeated the positive time trials

twice, with the seconds being: 2 s, 5 s, 7 s, 10 s, 12 s, and 15 s. For the negative time trials,

we only repeated these once, with the times being 1 s, 2 s, 3 s, 4 s, and 5 s. These negative

time trials are negative because of the negative direction. In total, we did seventeen time

trials, with which we marked with a post-it note and measured using meter sticks. 

​

​

Diagram of the Lab: 

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

Recorded Raw Data: 

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

Processed Raw Data:  

In order to get the most accurate results for this lab, for the positive time trials, we must calculate an average between the two time trials. For the negative time trials, because only one trial was done for each amount of time, we do not need to calculate an average. 

​

Said Calculations:

Graphs: 

For the final graphs, the data has been split up into positive and negative trials simply because the positive trials were done more than once with a different scale and amount of time. It's key to note that we started all timing as soon as the back wheels passed the starting line. 

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

For this positive position time graph, the equation in the form y = mx + b is X= 41.00t+ 25.29. The y-intercept indicates where the initial position is when x=0, or when no time has passed. So, the buggy has already traveled approximately 25.29 centimeters when the time is 0, meaning the length of the buggy is approximately 25.29 cm. The slope, in this case, presents the number of centimeters traveled per second, in this specific case, linearly. For every 1 second, the buggy travels approximately 41.00 cm. The speed of the buggy can be approximated then as 0.41 m/sec. The correlation is also 0.9978, indicating heavy error as the correlation is closer to 1, rather than 0. In addition, because some of these two data points for each time are very far off, it indicates error within measuring. 

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

​

For this negative position time graph, the equation in the standard from y= mx + b is X=-37.95t-20.25. The y-intercept indicates where the buggy begins when time equals zero. Because the y-intercept is -20.25 cm and we began the timer at the back wheels, we can infer the buggy's car length is approximately 20.25 cm. This is very close to the positive y-intercept from the positive time graph, indicating the buggy's true length is approximately between 20.25-25.29 cm.  In addition, the slope indicates how many centimeters traveled per second. The buggy travels approximately 37.95 cm per second in the negative direction. Therefore we can approximate that the true speed of the buggy is somewhere between 0.3795 m/sec-0.4100 m/sec. This correlation is once again close to -1, indicating a large margin of error within the points. This is most likely due to the use of only one trial per amount of time and incorrect measuring.  

​

Purpose of Labs Conclusion: 

The evidence of this lab indicated the speed of the buggy, approximately 39.475 cm/second, averaging the two slopes of the graphs. It also indicates the length of the buggy, 22.77 cm, again averaging the two y-intercepts. We can then state the way time affects the position of the buggy, as time passes, the buggy's position changes approximately 39.5 centimeters per second, either in a positive or negative direction, depending on the way we oriented the buggy compared to the starting ridge. In other situations, when we drop the buggy, we will be able to approximate the distance the buggy travels in any amount of seconds. 

Conclusion:

The raw data was somewhat consistent, with both of the slopes being around 40 cm and the y-intercepts around 25 cm. This indicates a high level of consistency within our data gathering methods.  Because the correlation is higher than normal, which indicates a high level of error within our group's data. With the raw data, we also had a large difference between the lengths of the same time trials, supporting this level of error. But overall, the correlation indicates linear progression within the points, meaning if we were to graph a velocity-time graph, the graph should be a flatline. We compared our results to some of the other groups, and we had very a very similar slope and y-intercept with one group, while the other two groups also had similar data, indicating there were 2 distinct speeds of the buggies. In addition, the fast buggy groups, (our group), both started the timer when the back wheels hit the starting point, affecting the y-intercept, while the slower buggy groups did not start with the back wheels, but with front wheels. Therefore, the y-intercept will be closer to zero. Similar to the Cart Motion Lab, we were able to find a distinct speed of these buggies, although a lot less accurate than the Cart Motion Lab, as we used video analytical technology. 

​

Evaluating Procedures:

There were several weaknesses within the procedure and the way we collected the data. First, a lot of the time the buggy dropped crooked, affecting the measurements, either shortening or lengthening it. Also, this crookedness also affected the measurement in which we utilized the meter sticks. In addition, when measuring, some of our post-it notes became loose, affecting the preciseness and measurement. 

​

Improving the Investigation: 

In order to improve this experiment, dropping the buggy more carefully or close to the wall for a straight reference.  In addition, being careful while measuring and being very precise is also key when doing these experiments. In addition, doing many trials for each time will ensure accuracy with our results when graphing. Comparing with other groups and learning about their procedure is also helpful. 

This is your Project description. A brief summary can help visitors understand the context of your work. Click on "Edit Text" or double click on the text box to start.

This is your Project description. Provide a brief summary to help visitors understand the context and background of your work. Click on "Edit Text" or double click on the text box to start.

This is your Project description. Provide a brief summary to help visitors understand the context and background of your work. Click on "Edit Text" or double click on the text box to start.

This is your Project description. A brief summary can help visitors understand the context of your work. Click on "Edit Text" or double click on the text box to start.