Chapter 6 - Probability

• Simple probability

  a measure of how likely an event is to happen

  P(event) = number of successful outcomes/total number of outcomes

  expected frequency of event A = P(A) x number of trials
• Experimental probability

  estimated probability = number of trials with successful outcomes/ total number of trials

  also called relative frequency

  more trials = more accurate
• Risk

  probability of event occurring for negative events

  risk = number of trials in which event happens/total number of trials

  Absolute risk : how likely an event is to happen (relative frequency)

  Relative risk : how much more likely an event is to happen for one group compared to another group

  relative risk = risk for those in the group/risk for those not in the group
• Mutually Exclusive and Exhaustive Events

  mutually exclusive events - CANNOT happen at the same time

  P(A or B) = P(A) + P(B)

  exhaustive events - contains ALL the possible outcomes

  P(A) + P(not A) = 1
• Addition Law

  also known as the general addition law, used for events that are not mutually exclusive (events that can happen together)

  P(A or B) = P(A) + P(B) - P(A and B)

  or = everything in both circles, including intersection

  and = the intersection/overlap
• Independent events

  unconnected events - the outcome of one does not affect the other

  P(A and B) = P(A) x P(B)
• Conditional Probability

  when one event affects the chances of another event happening

  P(BlA) = P(B given that A happens)

  P(BlA) = P(A and B)/P(B)

  P(A and B) = P(BlA) x P(A)

  if P(A) and P(AlB) are not equal, the events are not independent but are conditional