Lesson 2

• Probability - describes the level of certainty
• Probability can be expressed in decimal, fraction or percentage
• Probability Distribution is a table, graph, formula or notation which supplies the probability of a given outcome's occurrence
• Sample Space - set of all possible outcomes of an experiment
• Infinite Sample Space - if the number in the sample space is not finite
• Finite Sample Space - if the number in the sample space is finite or definite
• Null Sample Space - it has no element in the sample space
• Event - a subset of the sample space
• Event - set of all expected outcomes from the sample space
• SIMPLE Event - an event that contains only one sample point
• Experiment - simple process of noting an outcome
• Outcome - a direct measurement or answer obtained after an experiment
• n(S) - total number of events in the sample space
• Semantic Form - statement describing the elements of a set
• Roster Form - listing method
• Set Builder Notation - rule method
• Random Variables - a variable determined by chance denoted by x
• Random variable - a numerical description of the outcome of a statistical experiment
• Discrete random variable - countable possible outcomes
• Continuous random variable - take values on a continuous scale
• discrete probability distribution - probability mass function
• Discrete probability distribution - consists of values a random variable can assume
• The sum of all probabilities is equal to one
• P(E) = n(E)/n(S)
• Pascal's triangle - used to find the coefficients of binomial experiment
• Pascal's triangle - widely used in probability theory
• At Least - the sum of all probabilities larger than and including the given probability
• At Most - the sum of all probabilities less than and including the given probability