Problem $2/$ Mat labGrader $(20$ points$)($Core Course Outcome $4)$

Develop a Matlab function myFitExam that finds the best fit of the function

$p(t)=\frac{1}{a{t}^3+b{t}^2+ct+d}$

to a given set of data points $(t_i,p_i)$ using regression.

The function input shall be

$t$ : column vector of data values $t$

$p$ : column vector of data values $p$

The function output shall be

a: scalar containing the best fit coefficient $a$

b: scalar containing the best fit coefficient $b$

c: scalar containing the best fit coefficient $c$

$d$ : scalar containing the best fit coefficient $d$

In the function use only functions developed in this class in modules $1-4.$ You do not need to provide these functions

in your submission. They will be provided when assessing your function after the deadline.

Note: no assessments will be performed on your submitted function before the exam deadline. Scores on Canvas for

this problem before the exam has been fully graded are meaningless.

Required submission:

well commented function source code submitted to Matlab Grader using

Problem $3(15$ points$)($Core Course Outcome $4)$

Consider the following unsorted table of data points

Use your function myFitExam from problem $2$ to determine the coefficients $a,b,c,$ and $d$ that best fit the data. Print

the coefficients with at least $7$ significant digitis.

Required submission:

printout of script source code used to solve this problem in your Gradescope submission;