For example we had the frictionless car that helped reduce the particular friction greatly; also typically the ramp let the wheels fit into the plane which made the chaffing almost definitely According to be able to our graph above which usually is the points we have from our lab; all of us can declare as the angle of inclination raises then the average acceleration would increase. Except with regard to a few exceptions its is usually proved through our chart that the acceleration is elevated because the angle is improved, however for those exceptions we all may have the ability to say that error was involved because 30% is quite high.
We present our data using a couple of different methods and different numbers for each in addition to generally got different solutions. By looking at all in our data we can come to the conclusion that will the angle of tendency does not affect the particular acceleration. Like our Projectile Motion lab that we have done recently the particular projectile went a particular distance at a certain angle and then after altering the angle the distance would decrease after a while. All of us can say the exact same just for this Lab as that when the angle will be lower than 90 the acceleration would increase until the angle is over 90 and the speed will decrease again.
This is since if one examines this specific problem it makes sense. The car should go much faster until the bring if perpendicular to typically the ground and once you reduced the ramp to 180i?? then the car can barely have any acceleration considering there is no friction. In our Labrador we can calculate that will there is about 32% error which is very high, but for several reasons is true. We believe that this 32% mistake was taken because of random and systemic problems meaning that what all of us did made the error greater than it ought to be and also the particular proven fact that the instrument had been a bit hard to be able to work with.
One random error was that we definitely did not collect data and that will if we did acquire more data the outcomes would certainly be much more exact chances are they are. Another Random Mistake was the time that we used, we may have not used typically the time to our best success as it took very much time to prepare in addition to also take all the particular data down. A Systemic error that occurred has been with the frictionless car as the motion detector took a lot of time to detect the automobile and we had to measure from which height typically the car would be recognized. This took several before trails of which none of them were counted.
Our results from which we got from your lab compared to the gsin? outcome was not that a lot different, however there have been certain points that did not match up. Through my overall look I actually can say that the design and method of the particular investigation was good. Presently there were few weaknesses inside the lab, such as the movement detector taking time and energy to established up as well since getting it to operate appropriately which may have increased the error. Another weak point was our time supervision which was not upward to par, where inside this case we were at times working to fast and rushing a great deal since we didn’ t have much time left which affected our data tremendously.
Another weak point was when averaging the acceleration we only had constant acceleration for about 1 second in which often we averaged those numbers together. The precision associated with the data was decent as our motion detector was quite accurate. For that few weaknesses I got I can say there are usually simple solutions for all of them to be avoided next time. With the motion detecting I think we could actually very first find a proper elevation for both the ramp and the car in order to be placed at and whenever we raised the particular ramp we would boost the motion detector by the same amount.
Next was the particular time management where as always we could actually have ceased rushing and taken our own time even though it was scarce, this specific was because we got to do this lab during a time with constraints. The final weakness was with the acceleration and our solution is to boost typically the length of the bring and then let the car run regarding more some thus all of us will get a more detailed acceleration. To remove systemic/ random error next time we would need to make positive we have more period for that experiment and established up properly.