Expert ca you help me on this code please. See the correct result of output and have it run on your computer to see if it is work. You are welcome to comment every line so that I can understand better. Please help

import math def ClampInclusive (val, minval, maxval): return val maxval 5 6 7 8 9 def RemoveOutliers (vals, mean, stdev): trimmed = [] for lst in vals: newlst = [v for v in ist if (v mean - 2 * stdev)] trimmed.append(newlst) return trimmed def SampleEstimators(vals): ist = [v for ist in vals for v in ist] avg = sum(Lst) / len(lst) sdtemp = [(v - avg) * (v - avg) for v in Ist] sd = math.sqrt(sum(sdtemp) / len(sdtemp)) e return (avg, sd] 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 def reaction_rate(t, P, ea, nstdev = 2): mean = t[o] sd = t[1] mintemp = mean - nstdev * sd maxtemp = mean + nstdev * sd r = 8.3145 rate_range = [p * math.exp(-ea / (r * temp)) for temp in [mintemp, maxtemp, mean]] return rate_range if import_name__=="_main": print(ClampInclusive (185, 169.0, 181.0)) print(ClampInclusive (165, 169.0, 181.0)) print(ClampInclusive (180, 169.0, 181.0)) expt = [[174.9, 175.4, 175.7, 177.8, 178.3, 179, 176.8, 173.8, 175.1, 174.9, 179.2, 177.1, 180.2, 177.2, 173.4, 174.5, 178.3, 176.4, 173.6, 171.4, 174.9, 172.6, 173.8, 175, 175.4, 173.4, 174.3], [177.1, 174.6, 173.7, 176.3, 174, 175.3, 177, 171.8, 176.4, 174.6, 176.2, 174.4, 175.1, 176.7, 177.2, 178.5, 174.4, 175.5, 178.3, 179.6, 177.2, 172.6, 175, 175.4, 176.3, 175.1, 173.3, 178.6], [179.3, 174, 169.1, 174.1, 176.8, 174.5, 177.2, 176.4, 174.7, 173, 175, 172.4, 177.6, 175, 174.5, 172.5, 174.8, 179.3, 175.4, 172.4, 170.1, 170, 175.9, 178.9, 178.5, 178.1, 178.8, 174.1]] 42 e2 RemoveOutliers(expt, 175.5, 2) SampleEstimators(expt) t = B% print(reaction_rate(t, 10, 20)) 48 Correct Output: Homework 1 - SP21: An exercise in data processing. Clamp(185, 169.0, 181.0)=True Clamp(165, 169.0, 181.0)=True Clamp(180, 169.0, 181.0=False b) Experiment I had 3 outliers Refined experiment 1 data =[174.9, 175.4, 175.7, 177.8, 178.3, 179, 176.8, 173.8, 175.1, 174.9, 179.2, 177.1, 180.2, 177.2, 173.4, 174.5, 178.3, 176.4, 173.6, 171.4, 174.9, 172.6, 173.8, 175, 175.4, 173.4, 174.3] Experiment 2 had 2 outliers Refined experiment 2 data=[177.1, 174.6, 173.7, 176.3, 174, 175.3, 177, 171.8, 176.4, 174.6, 176.2, 174.4, 175.1, 176.7, 177.2, 178.5, 174.4, 175.5, 178.3, 179.6, 177.2, 172.6, 175, 175.4, 176.3, 175.1, 173.3, 178.6] Experiment 3 had 2 outliers Refined experiment 3 data=[179.3, 174, 169.1, 174.1, 176.8, 174.5, 177.2, 176.4, 174.7, 173, 175, 172.4, 177.6, 175, 174.5, 172.5, 174.8, 179.3, 175.4, 172.4, 170.1, 170, 175.9, 178.9, 178.5, 178.1, 178.8, 174.1] c) Experiment I stats: Mean = 175.6, StDev = 2.2 Experiment 2 stats: Mean = 175.7, StDev = 1.9 Experiment 3 stats: Mean = 175.1, StDev = 2.8 d) Experiment 1 Rates: Min = 4.26. Max = 4.34, Avg = 4.30 Experiment 2 Rates: Min = 4.27, Max = 4.34, Avg = 4.30 Experiment 3 Rates: Min = 4.25. Max = 4.35, Avg = 4.30 import math def ClampInclusive (val, minval, maxval): return val maxval 5 6 7 8 9 def RemoveOutliers (vals, mean, stdev): trimmed = [] for lst in vals: newlst = [v for v in ist if (v mean - 2 * stdev)] trimmed.append(newlst) return trimmed def SampleEstimators(vals): ist = [v for ist in vals for v in ist] avg = sum(Lst) / len(lst) sdtemp = [(v - avg) * (v - avg) for v in Ist] sd = math.sqrt(sum(sdtemp) / len(sdtemp)) e return (avg, sd] 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 def reaction_rate(t, P, ea, nstdev = 2): mean = t[o] sd = t[1] mintemp = mean - nstdev * sd maxtemp = mean + nstdev * sd r = 8.3145 rate_range = [p * math.exp(-ea / (r * temp)) for temp in [mintemp, maxtemp, mean]] return rate_range if import_name__=="_main": print(ClampInclusive (185, 169.0, 181.0)) print(ClampInclusive (165, 169.0, 181.0)) print(ClampInclusive (180, 169.0, 181.0)) expt = [[174.9, 175.4, 175.7, 177.8, 178.3, 179, 176.8, 173.8, 175.1, 174.9, 179.2, 177.1, 180.2, 177.2, 173.4, 174.5, 178.3, 176.4, 173.6, 171.4, 174.9, 172.6, 173.8, 175, 175.4, 173.4, 174.3], [177.1, 174.6, 173.7, 176.3, 174, 175.3, 177, 171.8, 176.4, 174.6, 176.2, 174.4, 175.1, 176.7, 177.2, 178.5, 174.4, 175.5, 178.3, 179.6, 177.2, 172.6, 175, 175.4, 176.3, 175.1, 173.3, 178.6], [179.3, 174, 169.1, 174.1, 176.8, 174.5, 177.2, 176.4, 174.7, 173, 175, 172.4, 177.6, 175, 174.5, 172.5, 174.8, 179.3, 175.4, 172.4, 170.1, 170, 175.9, 178.9, 178.5, 178.1, 178.8, 174.1]] 42 e2 RemoveOutliers(expt, 175.5, 2) SampleEstimators(expt) t = B% print(reaction_rate(t, 10, 20)) 48 Correct Output: Homework 1 - SP21: An exercise in data processing. Clamp(185, 169.0, 181.0)=True Clamp(165, 169.0, 181.0)=True Clamp(180, 169.0, 181.0=False b) Experiment I had 3 outliers Refined experiment 1 data =[174.9, 175.4, 175.7, 177.8, 178.3, 179, 176.8, 173.8, 175.1, 174.9, 179.2, 177.1, 180.2, 177.2, 173.4, 174.5, 178.3, 176.4, 173.6, 171.4, 174.9, 172.6, 173.8, 175, 175.4, 173.4, 174.3] Experiment 2 had 2 outliers Refined experiment 2 data=[177.1, 174.6, 173.7, 176.3, 174, 175.3, 177, 171.8, 176.4, 174.6, 176.2, 174.4, 175.1, 176.7, 177.2, 178.5, 174.4, 175.5, 178.3, 179.6, 177.2, 172.6, 175, 175.4, 176.3, 175.1, 173.3, 178.6] Experiment 3 had 2 outliers Refined experiment 3 data=[179.3, 174, 169.1, 174.1, 176.8, 174.5, 177.2, 176.4, 174.7, 173, 175, 172.4, 177.6, 175, 174.5, 172.5, 174.8, 179.3, 175.4, 172.4, 170.1, 170, 175.9, 178.9, 178.5, 178.1, 178.8, 174.1] c) Experiment I stats: Mean = 175.6, StDev = 2.2 Experiment 2 stats: Mean = 175.7, StDev = 1.9 Experiment 3 stats: Mean = 175.1, StDev = 2.8 d) Experiment 1 Rates: Min = 4.26. Max = 4.34, Avg = 4.30 Experiment 2 Rates: Min = 4.27, Max = 4.34, Avg = 4.30 Experiment 3 Rates: Min = 4.25. Max = 4.35, Avg = 4.30