算法导论 5.4-1 - newdye的专栏 - 博客频道 - CSDN.NET



算法导论 5.4-1 - newdye的专栏 - 博客频道 - CSDN.NET

1 问题

一个房间里必须要有多少人,才能让某人和你生日相同的概率至少为1/2?必须要有多少人,才能让至少两个人为7月4日的概率大于1/2?

2 分析与解答

P{n个人中有人与你生日相同} = 1-P{n个人中没有人与你生日相同} = 1-(364/365)n >=1/2

所以(364/365)n <= 1/2

n >= -1/log2 (364/365)

n >= -lg2/lg(364/365)

n >= 253

所以房间里必须有254人。

Xij = Iij{i与j生日都为7月4日}

E(Xij ) = P{i与j生日都是7月4日} = 1/3652

E(X) = ∑i=1n-1j=i+1n(1/3652 ) = n(n-1)/3652 >= 1/2

所以,n约为258


Read full article from 算法导论 5.4-1 - newdye的专栏 - 博客频道 - CSDN.NET


No comments:

Post a Comment

Labels

Algorithm (219) Lucene (130) LeetCode (97) Database (36) Data Structure (33) text mining (28) Solr (27) java (27) Mathematical Algorithm (26) Difficult Algorithm (25) Logic Thinking (23) Puzzles (23) Bit Algorithms (22) Math (21) List (20) Dynamic Programming (19) Linux (19) Tree (18) Machine Learning (15) EPI (11) Queue (11) Smart Algorithm (11) Operating System (9) Java Basic (8) Recursive Algorithm (8) Stack (8) Eclipse (7) Scala (7) Tika (7) J2EE (6) Monitoring (6) Trie (6) Concurrency (5) Geometry Algorithm (5) Greedy Algorithm (5) Mahout (5) MySQL (5) xpost (5) C (4) Interview (4) Vi (4) regular expression (4) to-do (4) C++ (3) Chrome (3) Divide and Conquer (3) Graph Algorithm (3) Permutation (3) Powershell (3) Random (3) Segment Tree (3) UIMA (3) Union-Find (3) Video (3) Virtualization (3) Windows (3) XML (3) Advanced Data Structure (2) Android (2) Bash (2) Classic Algorithm (2) Debugging (2) Design Pattern (2) Google (2) Hadoop (2) Java Collections (2) Markov Chains (2) Probabilities (2) Shell (2) Site (2) Web Development (2) Workplace (2) angularjs (2) .Net (1) Amazon Interview (1) Android Studio (1) Array (1) Boilerpipe (1) Book Notes (1) ChromeOS (1) Chromebook (1) Codility (1) Desgin (1) Design (1) Divide and Conqure (1) GAE (1) Google Interview (1) Great Stuff (1) Hash (1) High Tech Companies (1) Improving (1) LifeTips (1) Maven (1) Network (1) Performance (1) Programming (1) Resources (1) Sampling (1) Sed (1) Smart Thinking (1) Sort (1) Spark (1) Stanford NLP (1) System Design (1) Trove (1) VIP (1) tools (1)

Popular Posts