Formative Review #2
Quiz yourself by thinking what should be in
each of the black spaces below before clicking
on it to display the answer.
Help!
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| 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.)
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| Law of large numbers | is another way to state our definition of probability.
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| Sample Space | collection of all the possible outcomes of a probability experiment
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| Event | a collection of outcomes of a sample space
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| Compound Event | is an event that is formed by combining two or more events
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| simple event | any single outcome from a probability experiment
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| 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.
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| 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.
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| 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.
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| Complement | The complement of an event A is the event that A does not occur. (The events “Rain” and “No rain”)
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| Addition rule | The method of subtracting in order to adjust for double counting
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| mutually exclusive | impossible for both events to occur.
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| Multiplication rule | Use the General Multiplication Rule to compute probabilities of the form P(A and B).
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| independent events | if the occurrence of one does not affect the probability that the other event occurs
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| dependent events | If two events are not independent
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| 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
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| combinations | Each distinct group of objects that can be selected, without regard to order
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| A discrete random variable assigns probabilities to its inputs. |
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| The sum of the probabilities of a discrete random variable is equal to one. |
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| The expected value of a discrete random variable is equal to the mean. |
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| Probabilities are numbers that range between zero and one (0 P(A) 1). |
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| 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 |
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| Combinations can be used to find the odds of winning the lottery or how many groups can be formed. |
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| 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. |
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| 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. |
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| The range a probability will fall within is | 0 < P(x) < 1
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| A probability distribution gives the probability for each value of the random variable | True
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| A discrete random variable has either a finite number of values or a countable number of values. | True
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| Arrangements or sequences where order does not matter are called permutations. | False
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| The Empirical approach to probability is when you run an experiment and check the outcome to estimate the probability of a similar experiment. | True
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| 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
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| A person can be convicted at a legal trial exclusively on probabilities. | False
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| Random variable | a numerical outcome of a probability experiment.
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| 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
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| 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.
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| probability distribution | for a discrete random variable specifies the probability for each possible value of the random variable.
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| Expected value | Another name for the mean of a random variable
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Created by:
rjoljo82
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