statics 썸네일형 리스트형 Day 3: Bayes' Theorem HackerRank Day 3: Bayes' Theorem(베이지안 정리): P( A | B ) denotes the probability of the occurrence of A given that B has occurred ( B가 발생하면, A가 발생 할 확률 )P( B | A ) denotes the probability of the occurrence of B given that A has occurred ( A가 발생하면, B가 발생 할 확률 ) Let A and B be two events such that P( A | B ) and P( B | A ),A와 B가 P( A | B ) 그리고 P( B | A ) 라면, 더보기 Day 3: Conditional Probability, Bayes' Theorem HackerRank Day 3: Conditional Probability(조건부 확률):This is defined as the probability of an event occurring, assuming that one or more other events have already occurred.조건부 확률은 하나 이상의 사건이 이미 일어난 후에 어떠한 사건이 발생할 확률이다. Two events, A and B are considered to be independent if event A has no effect on the probability of event B.사건 A가 사건 B에 영향을 미치지 않는다면, 두사건 A와 B는 독립적이다. If events A and B are not indep.. 더보기 Day 0: mean, median, mode, weighted mean HackerRank 10 days of statistics: Day 0 note taking This is just for practice, can make it much shorter with some packages like numpy, scipy.array = [n1, n2 .... nN]type(n) == intN = len(array) Mean: sum( all N element in array) / N Median: middle element in a sorted array. If a number of N is even, then you have two elements in the middle of the array.an average of those two elements is median... 더보기 이전 1 다음