This is my fourth lecture notes about biostatistic, the previous notes, told us about the data presentation ( graphs, polygon, bar chart, histogram and etc. Probability topic will discuss about what happen when we roll a die or tossing a coin, in my opinion this topic will use to help us when we estimate the real distribution in population using several sample. the professor said that this topic is useful to expect the probability when we doing research in large population and doesn’t know about the real population distribution.
This is some keyword that used in this topic, I think I should remember it well 😀
- Random Experiment: the process of observing outcome of a chance event
- Elementary outcome : all possible result of the random eperiment
- Sample space: the set or collection of the elementary outcomes.
- Probability: numerical weight which measures the likelihood of it’s occurring.
When we toss the coin, head and tails are equal likely so we we assign them both the probability 0.5, P(H) = P(T) = 0.5. In the roll of two dice, 36 elementary outcomes occur all equally likely 1/36.
Logical Operation: we can combine events ro make other events
- Intersection of two events A and B, we can write B : A ∩ B ( A and B)
- Union of A and B –> A ∪ B
- Complement of A: not A: A c
When we have  problem with the probability statement, dealing with complexity of logical, we can use table to facilitate spreading probability, it is helpful to look at each event rules.
Conditional  ProbabilityÂ
Conditional probability that event a will occur, given the condition that event c has already occur, P ( A | C ) : say “probability if A given C”