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Formative Review #2
| Term | Definition |
|---|---|
| Probability | of an event is the proportion of times the event occurs in the long run, as a probability experiment is repeated over and over again. (Can only be positive numbers.) |
| Law of large numbers | is another way to state our definition of probability. |
| Sample Space | collection of all the possible outcomes of a probability experiment |
| Event | a collection of outcomes of a sample space |
| Compound Event | is an event that is formed by combining two or more events |
| simple event | any single outcome from a probability experiment |
| Classical probability | the frequency of an event occurs divided by total number of possible outcomes. This can only be used when all events are equally likely. |
| Empirical probability | the ratio of the number of outcomes in which a specified event occurs to the total number of trials, not in a theoretical sample space but in an actual experiment. |
| Relative frequency | the ratio of the number of times an event occurs to the number of occasions on which it might occur in the same period. |
| Complement | The complement of an event A is the event that A does not occur. (The events “Rain” and “No rain”) |
| Addition rule | The method of subtracting in order to adjust for double counting |
| mutually exclusive | impossible for both events to occur. |
| Multiplication rule | Use the General Multiplication Rule to compute probabilities of the form P(A and B). |
| independent events | if the occurrence of one does not affect the probability that the other event occurs |
| dependent events | If two events are not independent |
| permutations | r items chosen from n items is an ordering of the r items. It is obtained by choosing r items from a group of n items, then choosing an order for the r items |
| combinations | Each distinct group of objects that can be selected, without regard to order |
| A discrete random variable assigns probabilities to its inputs. | |
| The sum of the probabilities of a discrete random variable is equal to one. | |
| The expected value of a discrete random variable is equal to the mean. | |
| Probabilities are numbers that range between zero and one (0 P(A) 1). | |
| The multiplication rule can be used to find probabilities involving rolls of dice, how many different car keys can be made from a single key blank, the odds of getting true-false questions correct, or probability of restaurant reservations (all independen | |
| Combinations can be used to find the odds of winning the lottery or how many groups can be formed. | |
| The binomial probability formula can be used to find the probability of getting a certain number of girls/boys in a given number of births or number of defective items in a lot. | |
| Permutations can be used to find the number of different seating arrangements possible or the number of different batting line-ups that are possible for a baseball team. | |
| The range a probability will fall within is | 0 < P(x) < 1 |
| A probability distribution gives the probability for each value of the random variable | True |
| A discrete random variable has either a finite number of values or a countable number of values. | True |
| Arrangements or sequences where order does not matter are called permutations. | False |
| The Empirical approach to probability is when you run an experiment and check the outcome to estimate the probability of a similar experiment. | True |
| If a garage door opener has one set of 10 switches where the switches could be in one of three positions, a person could set all possible positions in less than ten minutes.(one position per second). | False |
| A person can be convicted at a legal trial exclusively on probabilities. | False |
| Random variable | a numerical outcome of a probability experiment. |
| Discrete random variable | are random variables whose possible values can be listed. The list may be infinite — for example, the list of all whole numbers |
| Continuous random variable | are random variables that can take on any value in an interval. The possible values of a continuous variable are not restricted to any list. |
| probability distribution | for a discrete random variable specifies the probability for each possible value of the random variable. |
| Expected value | Another name for the mean of a random variable |
Created by:
rjoljo82
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