By Hyeonmi Lee
12. spreadsheet Exploration

 

number of cout

values measured
1 1.00083255767822
2 1.06538569927216
3 1.10224843025208
4 1.10519051551819
5 1.08528816699982
6 1.0466947555542
7 0.998063564300537
8 0.954278230667114
9 0.89024430513382
10 0.818768620491028
11 0.715622127056122
12 0.619917392730713
13 0.532865941524506
14 0.46727442741394
15 0.416220366954803
16 0.393029719591141
17 0.391299068927765
18 0.393202781677246
19 0.391299068927765
20 0.421585381031036
21 0.461217164993286
22 0.511752009391785
23 0.584093034267426
24 0.737947463989258
25 0.768060684204102
26 0.837978839874268
27 0.903570294380188
28 0.957393407821655
29 1.0323303937912
30 1.03302264213562
31 1.0392529964447
32 1.02869606018066
33 1.00169789791107
34 0.96223920583725
35 0.922088205814362
36 0.869649648666382
37 0.802673637866974
38 0.720467925071716
39 0.649338364601135
40 0.56574821472168

 

 

number of cout (x) values measured Y= 0.7+(1/35)*EXP(-x/200)*(12*cos(3/13*x) +9*sin(3/13*x)
1 1.00083255767822 1.08517851071617
2 1.06538569927216 1.11178992838225
3 1.10224843025208 1.12179142858463
4 1.10519051551819 1.11495129438646
5 1.08528816699982 1.09170860749617
6 1.0466947555542 1.05314914529053
7 0.998063564300537 1.00095584845089
8 0.954278230667114 0.937336078321571
9 0.89024430513382 0.864928782301503
10 0.818768620491028 0.786695452061028
11 0.715622127056122 0.70579936403048
12 0.619917392730713 0.62547801204714
13 0.532865941524506 0.548913863415715
14 0.46727442741394 0.479108585129215
15 0.416220366954803 0.41876569804546
16 0.393029719591141 0.370186232953684
17 0.391299068927765 0.335181400871814
18 0.393202781677246 0.315005574647671
19 0.391299068927765 0.310312039916687
20 0.421585381031036 0.321133045229336
21 0.461217164993286 0.34688470143543
22 0.511752009391785 0.386396288600383
23 0.584093034267426 0.437962564318425
24 0.737947463989258 0.499416768287295
25 0.768060684204102 0.568221219451128
26 0.837978839874268 0.641571734600782
27 0.903570294380188 0.716511586230497
28 0.957393407821655 0.790050381417857
29 1.0323303937912 0.859283094116575
30 1.03302264213562 0.921504524600751
31 1.0392529964447 0.97431468833588
32 1.02869606018066 1.0157110413422
33 1.00169789791107 1.04416401233894
34 0.96223920583725 1.05867300968113
35 0.922088205814362 1.05880087429139
36 0.869649648666382 1.04468562551625
37 0.802673637866974 1.0170292596195
38 0.720467925071716 0.977064273862512
39 0.649338364601135 0.926499466561602
40 0.56574821472168 0.867447370681739
41 0.505521714687347 0.802336384085946
42 0.456717491149902 0.733811236514874
43 0.421931505203247 0.664625860100584
44 0.399952292442322 0.597532991278785
45 0.400990694761276 0.535174918641031
46 0.419335544109344 0.479979701857308
47 0.45291006565094 0.434066926601105
48 0.491849601268768 0.399166641450886

To see the best-fit graph, you should click here!!

 

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