Statistical Probability Syllabus-theory
id=”tw-target-text” class=”tw-data-text tw-text-large XcVN5d tw-ta” dir=”ltr” data-placeholder=”Bản dịch”>MISSIONS AND EVENTS 1.2.1 Concepts Experiment: Apply a specified set of conditions on the subject to observe a phenomenon some. Random Trials:
These are tests that satisfy two properties – I don’t know what the outcome will be. – All possible outcomes can be determined. Event:
A possible outcome in an experiment. Example
1.5: Random tests: toss a coin, toss a dice, draw a card in deck of 52 cards. 1.2.2 Classification of events and relationships between events: Certain Event: An event that is certain to occur in an experiment. Symbol:
W Example 1.6: Toss a die. Let A be the event that the dice appear with a small number of dots more than or equal to 6. Then we say that A is a certain event, A = W. Impossible Event: An event that cannot occur in an experiment.
Symbol: Example 1.7:
Toss a die. Let B be the event that the dice appear 7 dots. Then I say A is an impossible event, A = . Random Event: An event that may or may not occur in an experiment. Symbols: A, B, C,… A ,A1 2
1.3 DEFINITION OF PROBABILITY
1.3.1 Classical definition of probability Suppose an experiment has n equally likely primary events, of which there are m events favorable primary for event A.
Then the probability of event A is defined by following formula: P(A) = n m Example 1.19: Randomly roll a dice.
Find the probability that the dice appear on the top is even.
Guide to Probability Theory and Statistics 5 Solution: Call Ai the event that appears on the top of the dot.Let A be the event that the top surface is even, we have A = A2 A4A6 When the dice are toss, there are 6 possible events of which 3 are positive in favor of A should P(A) = n m = 6 3 = 0.5
