exercise 1:
[1, 2, 3, 4, 5, 6, 7, 8, 9, 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, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100]
exercise 2:
[1, 2, 3, 4, 5, 6, 7, 8, 9, 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, 42, 43, 44, 45, 46, 47, 48, 49, 50]
exercise 3:
0
1
2
3
4
5
6
7
8
9
10
exercise 4:
3.16227766017
4.472135955
5.47722557505
6.32455532034
exercise 7:
the line mult3.append(3*n) appends the empty list (mult3) with the values from the nums list, multiplied by 3
[3, 6, 9, 12, 15]
[3, 6, 9, 12, 15]
exercise 8:
[4, 8, 12, 16, 20, 24, 28, 32, 36, 40]
exercise 9:
Plot of multiples of 4:
exercise 10
[0.000000000000000, 10, 1.80000000000000, 0.360000000000000]
[0.200000000000000, 10.3600000000000, 1.80000000000000, 0.360000000000000]
[0.400000000000000, 10.7200000000000, 1.80000000000000, 0.360000000000000]
[0.600000000000000, 11.0800000000000, 1.80000000000000, 0.360000000000000]
[0.800000000000000, 11.4400000000000, 1.80000000000000, 0.360000000000000]
[1.00000000000000, 11.8000000000000, 1.80000000000000, 0.360000000000000]
[1.20000000000000, 12.1600000000000, 1.80000000000000, 0.360000000000000]
[1.40000000000000, 12.5200000000000, 1.80000000000000, 0.360000000000000]
[1.60000000000000, 12.8800000000000, 1.80000000000000, 0.360000000000000]
[1.80000000000000, 13.2400000000000, 1.80000000000000, 0.360000000000000]
[2.00000000000000, 13.6000000000000, 1.80000000000000, 0.360000000000000]
[2.20000000000000, 13.9600000000000, 1.80000000000000, 0.360000000000000]
[2.40000000000000, 14.3200000000000, 1.80000000000000, 0.360000000000000]
[2.60000000000000, 14.6800000000000, 1.80000000000000, 0.360000000000000]
[2.80000000000000, 15.0400000000000, 1.80000000000000, 0.360000000000000]
[3.00000000000000, 15.4000000000000, 1.80000000000000, 0.360000000000000]
[3.20000000000000, 15.7600000000000, 1.80000000000000, 0.360000000000000]
[3.40000000000000, 16.1200000000000, 1.80000000000000, 0.360000000000000]
[3.60000000000000, 16.4800000000000, 1.80000000000000, 0.360000000000000]
[3.80000000000000, 16.8400000000000, 1.80000000000000, 0.360000000000000]
[4.00000000000000, 17.2000000000000, 1.80000000000000, 0.360000000000000]
[4.20000000000000, 17.5600000000000, 1.80000000000000, 0.360000000000000]
[4.40000000000000, 17.9200000000000, 1.80000000000000, 0.360000000000000]
[4.60000000000000, 18.2800000000000, 1.80000000000000, 0.360000000000000]
[4.80000000000000, 18.6400000000000, 1.80000000000000, 0.360000000000000]
[5.00000000000000, 19.0000000000000, 1.80000000000000, 0.360000000000000]
[5.20000000000000, 19.3600000000000, 1.80000000000000, 0.360000000000000]
[5.40000000000000, 19.7200000000000, 1.80000000000000, 0.360000000000000]
[5.60000000000000, 20.0800000000000, 1.80000000000000, 0.360000000000000]
[5.80000000000000, 20.4400000000000, 1.80000000000000, 0.360000000000000]
[6.00000000000000, 20.8000000000000, 1.80000000000000, 0.360000000000000]
[6.20000000000000, 21.1600000000000, 1.80000000000000, 0.360000000000000]
[6.40000000000000, 21.5200000000000, 1.80000000000000, 0.360000000000000]
[6.60000000000000, 21.8800000000000, 1.80000000000000, 0.360000000000000]
[6.80000000000000, 22.2400000000000, 1.80000000000000, 0.360000000000000]
[7.00000000000000, 22.6000000000000, 1.80000000000000, 0.360000000000000]
[7.20000000000000, 22.9600000000000, 1.80000000000000, 0.360000000000000]
[7.40000000000000, 23.3200000000000, 1.80000000000000, 0.360000000000000]
[7.60000000000000, 23.6800000000000, 1.80000000000000, 0.360000000000000]
[7.80000000000000, 24.0400000000000, 1.80000000000000, 0.360000000000000]
[8.00000000000000, 24.4000000000000, 1.80000000000000, 0.360000000000000]
[8.20000000000000, 24.7600000000000, 1.80000000000000, 0.360000000000000]
[8.40000000000000, 25.1200000000000, 1.80000000000000, 0.360000000000000]
[8.60000000000000, 25.4800000000000, 1.80000000000000, 0.360000000000000]
[8.80000000000000, 25.8400000000000, 1.80000000000000, 0.360000000000000]
[9.00000000000000, 26.2000000000000, 1.80000000000000, 0.360000000000000]
[9.20000000000000, 26.5600000000000, 1.80000000000000, 0.360000000000000]
[9.40000000000000, 26.9200000000000, 1.80000000000000, 0.360000000000000]
[9.60000000000000, 27.2800000000000, 1.80000000000000, 0.360000000000000]
[9.80000000000000, 27.6400000000000, 1.80000000000000, 0.360000000000000]
[10.0000000000000, 28.0000000000000, 1.80000000000000, 0.360000000000000]
exercise 11
exercise 12
exercise 13
exercise 14
exercise 15
in order to generate more accurate graphs we must make the step size sufficiently small
exercise 16
(J, R)