题目：
一个奖励，每次抽取行为拿到奖励的概率为A%，若未抽取到，则下一次抽取行为拿到奖励的概率+B%，用excel建模，计算出抽到奖励所需的次数期望值C。
要求：A,B可以自由输入，通过excel模型自动运算出C
说明：抽奖概率最高为100%。超出则抽奖必中
| 初始概率A% | 10 | 0.1 | |||
| 概率增量B% | 5 | 0.05 | |||
| 期望次数C | 4.519562722 | ||||
| 抽取次数（n） | 当前成功概率 | 当前失败概率 | 前n-1次全失败概率 | 第n次成功概率 | 期望贡献值 |
| 1 | 0.1 | 0.9 | 1 | 0.1 | 0.1 |
| 2 | 0.15 | 0.85 | 0.9 | 0.135 | 0.27 |
| 3 | 0.2 | 0.8 | 0.765 | 0.153 | 0.459 |
| 4 | 0.25 | 0.75 | 0.612 | 0.153 | 0.612 |
| 5 | 0.3 | 0.7 | 0.459 | 0.1377 | 0.6885 |
| 6 | 0.35 | 0.65 | 0.3213 | 0.112455 | 0.67473 |
| 7 | 0.4 | 0.6 | 0.208845 | 0.083538 | 0.584766 |
| 8 | 0.45 | 0.55 | 0.125307 | 0.05638815 | 0.4511052 |
| 9 | 0.5 | 0.5 | 0.06891885 | 0.034459425 | 0.31013483 |
| 10 | 0.55 | 0.45 | 0.034459425 | 0.018952684 | 0.18952684 |
| 11 | 0.6 | 0.4 | 0.015506741 | 0.009304045 | 0.10234449 |
| 12 | 0.65 | 0.35 | 0.006202697 | 0.004031753 | 0.04838103 |
| 13 | 0.7 | 0.3 | 0.002170944 | 0.001519661 | 0.01975559 |
| 14 | 0.75 | 0.25 | 0.000651283 | 0.000488462 | 0.00683847 |
| 15 | 0.8 | 0.2 | 0.000162821 | 0.000130257 | 0.00195385 |
| 16 | 0.85 | 0.15 | 3.25642E-05 | 2.76795E-05 | 0.00044287 |
| 17 | 0.9 | 0.1 | 4.88462E-06 | 4.39616E-06 | 7.4735E-05 |
| 18 | 0.95 | 0.05 | 4.88462E-07 | 4.64039E-07 | 8.3527E-06 |
| 19 | 1 | 0 | 2.44231E-08 | 2.44231E-08 | 4.6404E-07 |
| 20 | 1 | 0 | 0 | 0 | 0 |
| 21 | 1 | 0 | 0 | 0 | 0 |
| 22 | 1 | 0 | 0 | 0 | 0 |
| 23 | 1 | 0 | 0 | 0 | 0 |
| 24 | 1 | 0 | 0 | 0 | 0 |
| 25 | 1 | 0 | 0 | 0 | 0 |
| 26 | 1 | 0 | 0 | 0 | 0 |
| 27 | 1 | 0 | 0 | 0 | 0 |
| 28 | 1 | 0 | 0 | 0 | 0 |
| 29 | 1 | 0 | 0 | 0 | 0 |
| 30 | 1 | 0 | 0 | 0 | 0 |
| 31 | 1 | 0 | 0 | 0 | 0 |
| 32 | 1 | 0 | 0 | 0 | 0 |
| 33 | 1 | 0 | 0 | 0 | 0 |
| 34 | 1 | 0 | 0 | 0 | 0 |
| 35 | 1 | 0 | 0 | 0 | 0 |
| 36 | 1 | 0 | 0 | 0 | 0 |
| 37 | 1 | 0 | 0 | 0 | 0 |
| 38 | 1 | 0 | 0 | 0 | 0 |
| 39 | 1 | 0 | 0 | 0 | 0 |
| 40 | 1 | 0 | 0 | 0 | 0 |
| 41 | 1 | 0 | 0 | 0 | 0 |
| 42 | 1 | 0 | 0 | 0 | 0 |
| 43 | 1 | 0 | 0 | 0 | 0 |
| 44 | 1 | 0 | 0 | 0 | 0 |
| 45 | 1 | 0 | 0 | 0 | 0 |
| 46 | 1 | 0 | 0 | 0 | 0 |
| 47 | 1 | 0 | 0 | 0 | 0 |
| 48 | 1 | 0 | 0 | 0 | 0 |
| 49 | 1 | 0 | 0 | 0 | 0 |
| 50 | 1 | 0 | 0 | 0 | 0 |
| 51 | 1 | 0 | 0 | 0 | 0 |
| 52 | 1 | 0 | 0 | 0 | 0 |
| 53 | 1 | 0 | 0 | 0 | 0 |
| 54 | 1 | 0 | 0 | 0 | 0 |
| 55 | 1 | 0 | 0 | 0 | 0 |
| 56 | 1 | 0 | 0 | 0 | 0 |
| 57 | 1 | 0 | 0 | 0 | 0 |
| 58 | 1 | 0 | 0 | 0 | 0 |
| 59 | 1 | 0 | 0 | 0 | 0 |
| 60 | 1 | 0 | 0 | 0 | 0 |
| 61 | 1 | 0 | 0 | 0 | 0 |
| 62 | 1 | 0 | 0 | 0 | 0 |
| 63 | 1 | 0 | 0 | 0 | 0 |
| 64 | 1 | 0 | 0 | 0 | 0 |
| 65 | 1 | 0 | 0 | 0 | 0 |
| 66 | 1 | 0 | 0 | 0 | 0 |
| 67 | 1 | 0 | 0 | 0 | 0 |
| 68 | 1 | 0 | 0 | 0 | 0 |
| 69 | 1 | 0 | 0 | 0 | 0 |
| 70 | 1 | 0 | 0 | 0 | 0 |
| 71 | 1 | 0 | 0 | 0 | 0 |
| 72 | 1 | 0 | 0 | 0 | 0 |
| 73 | 1 | 0 | 0 | 0 | 0 |
| 74 | 1 | 0 | 0 | 0 | 0 |
| 75 | 1 | 0 | 0 | 0 | 0 |
| 76 | 1 | 0 | 0 | 0 | 0 |
| 77 | 1 | 0 | 0 | 0 | 0 |
| 78 | 1 | 0 | 0 | 0 | 0 |
| 79 | 1 | 0 | 0 | 0 | 0 |
| 80 | 1 | 0 | 0 | 0 | 0 |
| 81 | 1 | 0 | 0 | 0 | 0 |
| 82 | 1 | 0 | 0 | 0 | 0 |
| 83 | 1 | 0 | 0 | 0 | 0 |
| 84 | 1 | 0 | 0 | 0 | 0 |
| 85 | 1 | 0 | 0 | 0 | 0 |
| 86 | 1 | 0 | 0 | 0 | 0 |
| 87 | 1 | 0 | 0 | 0 | 0 |
| 88 | 1 | 0 | 0 | 0 | 0 |
| 89 | 1 | 0 | 0 | 0 | 0 |
| 90 | 1 | 0 | 0 | 0 | 0 |
| 91 | 1 | 0 | 0 | 0 | 0 |
| 92 | 1 | 0 | 0 | 0 | 0 |
| 93 | 1 | 0 | 0 | 0 | 0 |
| 94 | 1 | 0 | 0 | 0 | 0 |
| 95 | 1 | 0 | 0 | 0 | 0 |
| 96 | 1 | 0 | 0 | 0 | 0 |
| 97 | 1 | 0 | 0 | 0 | 0 |
| 98 | 1 | 0 | 0 | 0 | 0 |
| 99 | 1 | 0 | 0 | 0 | 0 |
| 100 | 1 | 0 | 0 | 0 | 0 |