Polynominal Regression Fit
figure_1a
figure_1b
figure_1c
The objective for the part of the assignment was to use already existing data and plot a fit to that data. Initially, I began to use different values to find a particular fit that would ensure some sort of flexibility for the measurement which would be conducted later on. The final outcome of this section produce and a polynomial fit which calculated the average and maximum error values of each point on the dataset. A total of 50 dataset was produced. (Figure_1c represents the best fit)
Polynominal Regression Fit using, N= 3:
Error calculated was very high.
Sum of errors in the dataset: [ 2535033.60000039,]
Number of values in the dataset: 50
Average error in the dataset: [ 50700.67200001,]
Calcuation of maximum error for entire dataset [ 145286.39999986,]
Polynominal Regression Fit using, N=5:
Error calculated was lower than other N values, with room for flexiability.
Sum of errors in the dataset: [ 0.00050403,]
Number of values in dataset: 50
Average error in the dataset: [ 1.00805828e-005,]
Calcuation of maximum error for entire dataset [ 5.41539630e-005,]
Code Sample(Python Generated)
Download code here: