Ass_Q1_Data is given below:

0.000000000000000 1.000000000000000e+00 1.000000000000000e-01 9.473345794633837e-01 2.000000000000000e-01 8.717692645074964e-01 3.000000000000000e-01 7.772143033626658e-01 4.000000000000000e-01 6.678195121136710e-01 5.000000000000000e-01 5.478378052517147e-01 6.000000000000001e-01 4.214962856364747e-01 7.000000000000001e-01 2.928779798011800e-01 8.000000000000000e-01 1.658167644457922e-01 9.000000000000000e-01 4.380745897730279e-02 1.000000000000000e+00 -7.006752430960801e-02 1.100000000000000e+00 -1.731941588273762e-01 1.200000000000000e+00 -2.634651541954515e-01 1.300000000000000e+00 -3.393009429937728e-01 1.400000000000000e+00 -3.996540417439741e-01 1.500000000000000e+00 -4.439979403107866e-01 1.600000000000000e+00 -4.723020253005058e-01 1.700000000000000e+00 -4.849943245726334e-01 1.800000000000000e+00 -4.829140690358755e-01 1.900000000000000e+00 -4.672562040963616e-01 2.000000000000000e+00 -4.395100481914666e-01 2.100000000000000e+00 -4.013942933948674e-01 2.200000000000000e+00 -3.547904783777365e-01 2.300000000000000e+00 -3.016769436840562e-01 2.400000000000000e+00 -2.440651110246459e-01 2.500000000000000e+00 -1.839397205857213e-01 2.600000000000000e+00 -1.232044221258532e-01 2.700000000000000e+00 -6.363385602277885e-02 2.800000000000000e+00 -6.833088458451092e-03 2.900000000000000e+00 4.579501071579510e-02 3.000000000000000e+00 9.307413008823960e-02 3.100000000000000e+00 1.340705607974241e-01 3.200000000000000e+00 1.681011057527252e-01 3.300000000000000e+00 1.947332544098501e-01 3.400000000000000e+00 2.137782127817739e-01 3.500000000000000e+00 2.252775362773108e-01 3.600000000000000e+00 2.294842374634509e-01 3.700000000000000e+00 2.268393309705332e-01 3.800000000000000e+00 2.179448335808668e-01 3.900000000000000e+00 2.035342601107877e-01 4.000000000000000e+00 1.844416469278751e-01 4.100000000000001e+00 1.615700974979271e-01 4.200000000000000e+00 1.358607815005197e-01 4.300000000000000e+00 1.082632345291039e-01 4.400000000000000e+00 7.970770327195577e-02 4.500000000000000e+00 5.108016561175512e-02 4.600000000000001e+00 2.320053059418585e-02 4.700000000000000e+00 -3.195606064806396e-03 4.800000000000001e+00 -2.747140529140460e-02 4.900000000000000e+00 -4.909930816296674e-02 5.000000000000000e+00 -6.766764161830624e-02 5.100000000000000e+00 -8.288341967000502e-02 5.199999999999999e+00 -9.457155293585150e-02 5.300000000000000e+00 -1.026707651175628e-01 5.399999999999999e+00 -1.072265857734071e-01 5.500000000000000e+00 -1.083818435058448e-01 5.600000000000000e+00 -1.063651221834908e-01 5.700000000000000e+00 -1.014776651947737e-01 5.800000000000000e+00 -9.407921959144201e-02 5.899999999999999e+00 -8.457330432135825e-02 6.000000000000000e+00 -7.339236590604738e-02 6.100000000000000e+00 -6.098325249587920e-02 6.199999999999999e+00 -4.779339504712447e-02 6.300000000000000e+00 -3.425803436142036e-02 6.400000000000000e+00 -2.078877693272193e-02 6.500000000000000e+00 -7.763702992134130e-03 6.600000000000000e+00 4.480811189716799e-03 6.699999999999999e+00 1.565645590866035e-02 6.800000000000000e+00 2.552749409393578e-02 6.900000000000000e+00 3.391342538869934e-02 7.000000000000000e+00 4.068987407713224e-02 7.100000000000000e+00 4.578781215628425e-02 7.199999999999999e+00 4.919126765422931e-02 7.300000000000000e+00 5.093369984623353e-02 7.400000000000000e+00 5.109324697759238e-02 7.500000000000000e+00 4.978706836786394e-02 7.600000000000000e+00 4.716501147498512e-02 7.699999999999999e+00 4.340283597303721e-02 7.800000000000000e+00 3.869522165799878e-02 7.900000000000000e+00 3.324877570699686e-02 8.000000000000000e+00 2.727523826456767e-02 8.100000000000000e+00 2.098506438978390e-02 8.199999999999999e+00 1.458153600380331e-02 8.300000000000001e+00 8.255530588000656e-03 8.400000000000000e+00 2.181044955125370e-03 8.500000000000000e+00 -3.488456623169428e-03 8.600000000000000e+00 -8.622829426453269e-03 8.699999999999999e+00 -1.311715764447872e-02 8.800000000000001e+00 -1.689279924611169e-02 8.900000000000000e+00 -1.989760309980040e-02 9.000000000000000e+00 -2.210535580944390e-02 9.100000000000000e+00 -2.351453322391687e-02 9.199999999999999e+00 -2.414644559552369e-02 9.300000000000001e+00 -2.404287577089249e-02 9.400000000000000e+00 -2.326331657865414e-02 9.500000000000000e+00 -2.188191681767172e-02 9.600000000000000e+00 -1.998424512772070e-02 9.699999999999999e+00 -1.766397780325956e-02 9.800000000000001e+00 -1.501961062020633e-02 9.900000000000000e+00 -1.215128636879433e-02 1.000000000000000e+01 -9.157819444367117e-03

For the signal given in the file "Ass 2 Q1 _data" text file, write a program/MATLAB script that will attempt to find the best fit curve (by having the least square error) using either normal equations or householder QR method. The models you must test are given in the table below e o Table 1 functions for curve fitting Question 1 f3(t) = For each curve you must find the coefficients that provide the least square error and provide the numerical value of the least square error for each curve. You must also provide the code as well as document your code with comments and clearly indicate the methods used in the code. For the signal given in the file "Ass 2 Q1 _data" text file, write a program/MATLAB script that will attempt to find the best fit curve (by having the least square error) using either normal equations or householder QR method. The models you must test are given in the table below e o Table 1 functions for curve fitting Question 1 f3(t) = For each curve you must find the coefficients that provide the least square error and provide the numerical value of the least square error for each curve. You must also provide the code as well as document your code with comments and clearly indicate the methods used in the code