# Results

Here are the final grades for the project. Note that the project gives a maximum 30 points out of the 100 points for the total grade. Note also that no matter the project grade, you still need to get at least 28/70 points (40%) in the final exam to pass the course.

Note that there were some errors in the project grades published last thursday. Hopefully, those errors are now fixed.

634938 0
654178 16
683942 27
698244 22
699049 26
705352 12
705428 24
705442 24
705708 30
707750 30
707767 24
707905 26
712651 8
715007 30
715066 20
716038 30
716438 12
716439 20
716443 28
716455 22
716460 15
716464 20
716467 28
716475 15
716486 30
716488 30
717867 21
719306 30
722284 30
722301 30
722380 28
722382 27
722386 30
722390 21
722391 25
722392 30
722393 25
722397 30
722398 28
722399 28
722401 21
724006 22
728394 27
728529 22
728628 22
730838 30
 Date Return date Assignment 2012-02-16 2012-03-08 Project

## LaTeX

If you want to typeset the project with LaTeX, you may use the following template to get started. This include

• Neville and Divided Difference tables
• Interpolation tables
• Graphs
• Python and Matlab code

For other help and introduction to LaTeX you may consult the LaTeX wikibook.

## Polynomial Interpolation with polyfit and polyval

I describe here usage of polyfit and its close friend polyval.

To obtain an interpolating polynomial, you would go as follows:

p = polyfit([0.,2.,1.], [2.,1.,1.], 2)

Do not forget the third argument, which is the degree of the polynomial that you wish to interpolate with. You should always use the number of interpolation points minus one (here 2 = 3-1).

Now that you have the polynomial p, you may evaluate it at various points as follows

polyval(p, 10) # value of the polynomial at x = 10

This is especially useful if you want to plot a polynomial. You would go as follows:

xs = linspace(-1,3,500) # 500 points between -1 and 3
ys = polyval(p, xs) # the y values
plot(xs,ys)