It was very difficult to avoid this error, as even the slightest bump would make it move. This bump could change incline of the reface by as much as 10 degrees. If it were tilted 10 degrees upwards, this would make it so there were weight and tension components in two dimensions. Using Newton’s Laws, was able to derive the following equation: By my calculations, this would change the first p value in column A to 0. 043, a difference of 130%. The second error in this experiment is the non-uniformity of the black surface from one end to the other.
Since the surface is not uniform, the value of PC is not constant. This means we are only finding an average value of p. This leads to inconsistencies of p, since the block will not always follow he exact same path on the surface. Another source of inconsistency was a “stuttering” effect of the block as it moved across the surface.
When we analyze side C of the block, the range of values for PC is 0. 0809 to 0. 1306. Using the average value from the slope of the best fit line, the percent difference between the high and average values is 41. %, while the percent difference between the low and average values is 6. 2%. This trend continues for the other faces of the block. From these percents, it shows that the values for PC are more accurate as the mass increases.
A more massive block/hanger would have greater inertia, and be less prone to the effects of the “stuttering” motion of the block down the surface. Questions for Thought 1) The value of sliding friction does depend on the normal force between the two objects. This is shown by the equation, .This is also shown by Table 2. Whenever the normal force increased, the frictional force increased. 2) The value of sliding friction between two objects does not depend on the area of contact between the two objects.
This is shown by my data in columns A and B. 3) The value of sliding friction between two objects does append on the materials that are in contact. This was shown by my data when I compared column C with columns A and B. 4) The percent differences are close to one another.My percent difference for the data in column A is 3. 56%.
My percent difference for the data in column B is 11. 1%. My percent difference for the data in column C is 11. 7%. These are reasonable percent differences when comparing an average value and using a best fit line. 5) I believe the slope of the best fit line gives a more accurate value for PC. When Excel creates a best fit line, it uses the method of least-squares for the line.
The least-squares fit accounts for the uncertainty in the experiment.An average does not account for uncertainty. This is the reason I believe the slope best fit line is more accurate than the average to find PC. 6) I would use rubber on one side of the block to reduce the error in measuring p. I believe by using a material of higher p, error will be reduced by being able to use higher numbers.
In general, when higher numbers are used, error is decreased. A material that is easy to find with a low p value is aluminum. We could attach aluminum foil to one of the surfaces to test yet another case for p.