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Scientists have previously demonstrated that ski wax has an effect on friction force. Our data has a general trend that shows how friction force will decrease with more wax. Despite the accurate trend, our data was not entirely precise, and we had sources of error and several outliers within our graph. The calculated average slope ended up at -0.05 / layer. Our slopes dependent variable, the coefficient of friction, depended on our independent variable, wax. This negative slope aligns with the focus of our experiment. It suggests that the average slope means there was less friction force on the ski as more layers of wax were added. The maximum and minimum slopes are proof of the errors in our experiment. However, we could successfully find trends based on our values for the coefficient of friction. The average slope line doesnt represent our data as well as it could, making it possible for a curved, negative exponential line to better represent it. This would only make sense if the wax made a large difference in friction force after adding the first few layers and then didnt make a difference in friction force after a certain amount of wax had filled in all the scratches on the bottom of the ski. The line of best fit shown on our graph runs through most of our error bars despite three outliers at 4, 6, and 10 layers of wax. Our maximum and minimum slopes have significantly different values from our line of best fit, this is mainly because the final data point is an outlier. And our outliers are due to the following errors.
As we mentioned previously, our data did not completely support our hypothesis that the friction force will decrease with more wax. An example of this is how it started to decrease from 0.18 N at the 1st layer to 0.07 N at the 4th layer, but then it increased back to 0.19 N at the 5th layer. In this case, we decided that the fourth layer is certainly an outlier, but that our overall experiment is correct.
Sources of error in this experiment could result from several incidents. The errors could be due to the amount of wax that was on the ski, and how much rubbed off based on the rough texture of the carpet we dragged it along. The carpet was not cleaned every day, so there could have been additional dirt and on the floor that got caught in the wax. The length of the string we used to tie the tip of the ski to the friction probe could have caused the ski to waiver left to right thus causing a path that wasnt parallel to the floor. This could have resulted in force against the grain of the ski. Another source of error was the assumption that the ski was not accelerating in the vertical direction, so the net force was 0. This error could be caused by the simple fact that we moved the ski manually. If the ski accelerated, we would need to alter our Newtons Law equations used throughout the experiment, as the net force would be mass multiplied by acceleration, not 0. This is why we needed to keep our velocity constant. An additional source of error could be the equipment used. The string used to tie the ski to the friction probe could not be perfectly even, dividing out the force to one side more than to the other. A failure to calibrate or zero the instrument is also a possible error. We could have also experienced an instrument drift. A lot of electronic instruments drift over time. The amount of drift is not always concerning, but can occasionally be of significance and therefore should be addressed.
Improvements that could be made to our experiment are as follows. We could clean the surface of the carpet before each layer of wax is added so that dirt wont potentially be caught in the wax. We could also ensure that the string we use is perfectly even, at a short length, and not in the skis path. To address potential problems with acceleration, we would ensure that the same person is moving the ski in the same area and keeping the velocity and length constant. To make sure we dont have a faulty zero, we can calibrate the equipment two times.
Although we can try to manage the errors, no physical quantity can be measured with perfect certainty. There are always errors in any measurement and it does not mean the experiment is wrong.
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