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### 66 Cards in this Set

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 Probability is defined as... The numeric value representing the change, likelihood or possibility that a particular even will occur. An event that is certain to happen has a probability of 1 An event that has NO certainty to happen has a probability of 0 The three types of priority are... A priori Empirical Subjective A Priori is defined as... Probability of an occurrence is based on prior knowledge of the process involved. When each outcome is equally likely, the probability is known as... A Priori The equation for 'A Priori' is # of ways the event can occur DIVIDED BY Total # of possible outcomes A example of A priori is... Choosing black or red from a deck of cards Empirical Probability is defined as... Probability that is based on observable data. Probability that is based on observable data is known as... Empirical Probability An example of Empirical Probability is... Surveys Each possible outcome of a variable is referred to as an event This is described by a single characteristic A simple event Each side of a dice is described as A simple event An event with two or more characteristics is defined as A Joint Event Getting two heads when you toss a coin is an example of a A Joint Event The complement of something is represented by An apostrophe (A' means complement of A) What are the complements of the following.... *Heads on a coin *Five dots on a die *Tails *Not getting five dots on a die The collection of all possible events is called the Sample Space (Heads & Tails on a coin) (One, Two, Three, Four, Five & Six on a die) Two things to help you visualize sample spaces are... Contingency tables and Venn Diagrams In a Venn Diagram, A U B means... the total area of A and B In a Venn Diagram, A n B means... the intersection of A and B A simple probability refers to the probability of occurrence of a Simple Event An event that consists of a set of Joint Probabilities is know as Marginal Probability When two events cannot occur at the same time it is called Mutually exclusive When there is a sex of events and one of the events must occur it is called Collectively exhaustive A coin toss is mutually exclusive because You cant have heads and tails at the same time. A coin toss is collectively exhaustive because If heads does not occur, tails must occur Male and Female, Heads and Tails are both what kinds of events Mutually exclusive and Collectively exhaustive When dealing with an OR problem with A and B as variables... the equation would look like.. P(A)+P(B) - P(A&B) Explain the following statement... P(A|B) = P(A and B) / P(B) The Probability of B given A is equal to the probability of A and B divided by the probability of A When dealing with an ALSO problem with A and B as variables... the equation would look like.. P(A|B) = P(A and B) / P(B) A decision tree is an alternative to A Contingency table When the outcome of one event does not affect the probability of occurrence of another even, the events are said to be Independent When dealing with dependence, if A and B percentages are equal then the events are... Independent When dealing with the Multiplication rule, multiply... The first possibility times -1 the second. (this is due to the first probability being subtracted from the second portion of the equation) A mathematical expression that defines the distribution of values for a continuous probability Probability density function The three types of distribution are... Normal, Uniform and Exponential This distribution is symmetrical and bell shaped. Normal Distribution. Normal Distribution has this type of visual... Bell shaped and symmetrical Most values tend to cluster around the mean when dealing with this type of distribution Normal Distribution During normal distribution, the vales tend to cluster around the... Mean During normal distribution, the mean is equal to the Median The Median is equal to the Mean during this type of distribution Normal There is normally no large positive or negative values when dealing with this type of distribution Normal Distribution A distribution that is shaped like a box is known as... Uniform Distribution During uniform distribution, each value has an equal probability of occurrence anywhere in the range of The smallest and largest value. Uniform distribution is symmetrical which means The Mean and the median are equal The skewed distribution is known as... Exponential Distribution When dealing with exponential distribution, it skews to the ______ and the _____is larger than the ________ Right, Mean is larger than the median The range of an exponential distribution is... Zero to positive infinity When dealing with exponential distribution, large values are... Unlikely! When dealing with normal distribution, the probability of a single value and not a range is ZERO During normal distribution, the interquartile range is equal to 1.33 standard deviations 'e' is equal to 2.718 'π" is equal to 3.1415 "μ" is equal to The Mean "σ" is equal to Standard deviation. the Stan How do you calculate "σ" (1) Find the mean (2) Subtract the mean from each single number to get a list of deviations (3) Square all these deviations (4) Sum all these deviations (5) Divide by one less than the total # of #'s (6) SQUARE ROOT of this number How do you calculate "μ" Calculated by adding up all the numbers and dividing by the # of #'s "Z" is equal to Any continuous variable where -INF < X < INF The transformation formula is... Z= X - µ DIVIDED BY σ Uniform Distribution, probability density function 1 DIVIDED BY b - a Uniform Distribution, probability density function...A and B... which is the larger function A is the MIN B is the MAX Uniform Distribution, Mean of the distribution µ = a+b DIVIDED BY 2 Uniform Distribution, standard deviation formula σ = SQUAREROOT (b-a)^2 DIVIDED BY 12