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The sum squared error has been evaluated for the n th degree of polynomial regression.
Figure 1.
Polynomial regression was evaluated on the raw data. The logarithmic regression was done for comparison purposes. However the equation for logarithmic regression was nonlinear.
Figure 2.
Problems that
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need to be
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tackled
- The initial turbidity is not the same as the clay dose turbidity (Experimental setup)
- Different type of slope plots for different degree, n of polynomial (Plots not shown) - not consistent
- Logarithmic regression is nonlinear
- The slope curve will be smoother n-1 th polynomial if plotted against smaller uniform ¿x
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- Saturation plot analysis - After this, will decide which regression line should we choose.
- Draw a smoother slope curve - using smaller uniform ¿x
- Get feedbacks from the Tube Floc group - We Rock!
- Tidy up the programming and make a list of constants used
March 7, 2008
Another example of how the data was analyzed (from previous experimental setup).
Alum = 35mg/L, initial NTU = 75 NTU, Flow rate = 1.443 mL/s
Figure 1. Raw Data
Figure 2. Turbidity vs. Terminal Velocity
Figure 3. Regression plots. Regression was done for up to the 10th degree of polynomial.
Figure 4. Sum squared error and R2 value