Drag lab

calculate the terminal velocity. We need to determine which of

the models fits the best( Fd=-KV 2 or Fd=-KV). We can do this by equaling this to mg by plotting each terminal velocity and the mass and doing both a linear and curve fit.

Procedure:
To carry out this experiment we added a sequence of drops into coffee filters. We stacked a few coffee filters to increase the mass without increasing the drag force. This process was repeated ten times, each time piling one filter. After we collected the data we could find the terminal velocity. We could find it regarding position or velocity.

M Vt Core.

1 0.9392 1

2 1.269 0.9996

3 1.533 0.9994

4 1.813 0.9998

5 2.011 0.9999

6 2.283 0.9995

7 2.358 0.9999

1

8 2.502 0.9998

9 2.711 0.9999

10 2.81 1

Analysis:

For the data obtained the model was found to fit the curve model better than the linear model. This was based on different correlation values as well. The linear model with a correlation value of 0.9741 and the curve fit with a correlation value of 0.997. The value for terminal velocity is true as well. We can prove that by finding the average of each linear fit,

2

which was 0.999. This number indicates that there might be some errors. One of them might be when selecting the different areas to calculate the linear regression or maybe error in the signal.

Conclusion:
In conclusion, the coffee filter has been demonstrated to be more suitable for the curve model, with a correlation value of 0,999 and has been fed the filters from sufficient height to meet and calculate the terminal velocity. This means that the Fd=-KV 2 fits the best. The key causes of error were the error in the linear regression selection of the data that did not match perfectly or do not have a 1 correlation value at curve fit.