Using the Secant method to create a Matlab script that shows the results for two different functions. One of the examples is shown below and make sure absolute relative error is less than 0.05% at the end of the result.

Example 1 Cont. Let us assume the initial guesses of the root of fx)-0 as x 0.02 andx-0.05 Iteration 1 The estimate of the root is 05-0.165(o.os)+3.993x10 o.0s-0.02) 0.05- = o.-0. 05-0.165 0.05 +3.993x10 " - 0.02-0.165 0.02 + 3.993 10 4 0.06461 The absolute relative approximate error |Eal at the end of iteration 1 is x 100 0.06461-0.05 0.06461 x 100 = 22.62% The number of significant digits at least correct is 0, as you need an absolute relative approximate error of 5% or less for one significant digits to be correct in your result Iteration 2 The estimate of the root is 6461-0.165(0.06461+3.993x1010.06461-0.05) 0.06461 64610.165(0.06461+3.993x10-0.05-0.165(0.05)+3.993x10 0.06241 The absolute relative approximate error |Eal at the end of iteration 2 is x 100 0.06241-0.06461 0.06241 x100 -3.525% The number of significant digits at least correct is 1, as you need an absolute relative approximate error of 5% or less . It ration 3 The estimate of the root is (0.0624 13-0. 165(0.06241)" + 3.993 x 10-4 .06241-0.06461) .0624-.16(0.06241+3.993x10-0.0s-0.165(0.06461+3993x10 0.06241- 0.06238 The absolute relative approximate error |Ea| at the end of iteration 3 is 100 Xy 0.06238-0.06241 100 0.06238 | = 0.0595% The number of significant digits at least correct is 5, as you need an absolute relative approximate error of 0.5% or less