[amp_mcq option1=”TRUE” option2=”nan” option3=”nan” option4=”nan” correct=”option1″]<\/p>\n
The correct answer is A. Conditional probability is a measure of the probability of an event given that another event has already occurred. It is calculated by dividing the probability of the two events occurring together by the probability of the first event occurring. For example, the conditional probability of getting heads on a coin flip after getting tails on the previous flip is $\\frac{1}{2}$, because the probability of getting heads and tails in any order is $\\frac{1}{2} \\times \\frac{1}{2} = \\frac{1}{4}$, and the probability of getting tails on the previous flip is $\\frac{1}{2}$.<\/p>\n
The other option, B, is false. The probability of an event is not affected by the occurrence of another event. For example, the probability of getting heads on a coin flip is still $\\frac{1}{2}$, even if you have already gotten heads on the previous flip.<\/p>\n","protected":false},"excerpt":{"rendered":"
[amp_mcq option1=”TRUE” option2=”nan” option3=”nan” option4=”nan” correct=”option1″]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[729],"tags":[],"class_list":["post-45968","post","type-post","status-publish","format-standard","hentry","category-machine-learning","no-featured-image-padding"],"yoast_head":"\n