Curve fitting
The following data points were found experimentally,
| x |
1 |
2 |
3 |
4 |
5 |
6 |
7 |
7.5 |
8 |
9 |
10 |
| y |
1 |
4 |
8 |
12 |
16 |
20 |
22 |
25 |
28 |
33 |
45 |
personalise this data by adding one intermediate point, with a value of y that fits into the general trend of the data. Then analyse the data using MATLAB and fit a number of linear curves through the results.
Submission
Fit the following curves through the data points,
1. straight line, ie y = a + bx
2. exponential equation, ie Y = aebx
3. power equation, ie y = aXb
What are the coefficients of the equations? Plot the experimental data along with the curves predicted by the linear regression analyses, and find the value of y at your data point using the three curve fitting schemes.
Discuss the results, and compare the accuracy of these three regression analyses by considering the coefficient of determination and standard error of the estimate for each.
You may use any MATLAB functions to check your answers.
Deadline
Assignments must be posted in the third year assignment postbox (at the end of the first floor corridor in the Robert Blackburn building), before 5.00 pm of the TUESDAY of the specified week.
Remember, assignments handed in late will only be able to receive a maximum of 40% -provided marked assignments have not been returned; and any two or more submissions which look similar, will share the marks between the collaborating partners.
Notes ...
- Include comments to fully explain the procedures used.
- Include an Introduction to describe what is going on and discuss and compare the results, it is ks not enough just to submit the results.
- Plot the graphs in a similar style to that used in the lectures.