Business Statistics-Test 3
Conditional Probability
probability of a particular event occurring, given that another event has occurred
Experiment
process that leads to the occurrence of one and only one of several possible results. An experiment has two or more possible results, and it is uncertain which will occur.
Joint Probability
a probability that measures the likelihood two or more events will happen concurrently
Empirical Probability
= Number of times the event occurs/Total number of observations
Multiplication Formula
Total number of outcomes= (m)(n)
Empirical Probability (or Relative Frequency)
the probability of an event happening is the fraction of the time similar events happened in the past. It is based on the number of times an event occurs as a proportion of a known number of trials.
Dependent
this is assumed if two events are not independent of one another.
Rules of Multiplication
use these to find the likelihood of two events happening
Odds
used to describe the likelihood of an event.
Complement Rule
used to determine the probability of an event occurring by subtracting the probability of the event not occurring from 1.
0!
zero factorial, is 1
Mutually Exclusive and Collectively Exhaustive
If the set of events is collectively exhaustive and the events are mutually exclusive, the sum of the probabilities is one.
Multiplication Formula
If there are "m" ways of doing one thing and "n" ways of doing another thing, there are "m"x"n" ways of doing both. (Two or more groups paired together)
Combination Formula
Order of selected objects IS NOT important. Formula to count the number of "r" object combinations from a set of "n" objects
Law of Large Numbers
Over a large number of trials, the empirical probability of an event will approach its true probability. (More observations will provide a more accurate estimate of the probability)
Special Rule of Addition
P (A or B)= P(A)+P(B)
Special Rule of Multiplication
P(A and B)= P(A)P(B)
General Rule of Multiplication
P(A and B)= P(A)P(BIA)
General Rule of Addition
P(A or B)= P(A)+P(B)-P(A and B)
Complement Rule
P(A)= 1-P(~A)
Classical Probability
Probability of an event= Number of favorable outcomes/ total number of possible outcomes
Inclusive
The expression P(A or B), suggests that A or B may occur. The use of "or" is termed as this...
Event
a collection of one or more outcomes of an experiment
Tree Diagram
a graph that is helpful in organizing calculations that involve several stages. Each segment in the tree is one stage of the problem. The branches of the tree are weighted by probabilities.
Outcome
a particular result of an experiment
Contingency Table
a table used to classify sample observations according to two or more identifiable categories or classes. (A cross-tabulation that simultaneously summarizes two variables of interest and their relationship.)
Probability
a value between zero and one, inclusive, describing the relative possibility (chance or likelihood) an event will occur. It is a number that describes the chance that something will happen. The closer a probability is to 0, the more unlikely that the event will happen.
Permutation
any arrangement of "r" objects selected from a single group of "n" possible objects. Order of selected objects IS important.
Permutation Formula
applied to find the possible number of outcomes when there is only one group of objects.
Collectively Exhaustive
at least one of the events must occur when an experiment is conducted.
Classical Probability
based on the assumptions that the outcomes of an experiment are equally likely.
inferential statistics
computing the chance that something will occur in the future
Special Rule of Addition
if two events A and B are mutually exclusive, the probability of one or the other event's occurring equals the sum of their probabilities.
Combination Formula
nCr= n!/r!(n-r)!
Permutation Formula
nPr= n!/(n-r)!
Special Rule of Multiplication
requires that two events (A and B) are independent, the probability that A and B will both occur is found by multiplying the two probabilities.
Probability Theory
science of uncertainty. It is important that all known risks be scientifically evaluated.
Objective Probability
subdivided into 1) classical probability and (2) empirical probability
General Rule of Multiplication
the conditional probability is required to compute the joint probability of two events that are not independent.
Subjective Probability
the likelihood (probability) of a particular event happening that is assigned by an individual based on whatever information is available.
Independence
the occurrence of one event has no effect on the probability of the occurrence of another event.
Mutually Exclusive
the occurrence of one event means that none of the other events can occur at the same time. (Example: gender)
General Rule of Addition
the outcomes of an experiment may not be mutually exclusive. The probability cannot be greater than 1.
