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Bus Stats Exam 2
Business Stats Ch 20 and 4
| Term | Definition |
|---|---|
| Aggregate Price Index | A composite price index based on the prices of a group of items. |
| Consumer Price Index | A monthly price index that uses the price changes in a market basket of consumer goods and services to measure the changes in consumer prices over time. |
| Dow Jones Average | Aggregate price indexes designed to show price trends and movements associated with common stocks |
| Industrial Production Index | A quantity index designed to measure changes in the physical volume or production levels of industrial goods over time |
| Laspeyres Index | A weighted aggregate price index in which the weight for each item is its base-period quantity |
| Paasche Index | A weighted aggregate price index in which the weight for each item is its current-period quantity |
| Price Relative | A price index for a given item that is computed by dividing a current unit price by a base-period unit price and multiplying the result by 100 |
| Producer Price Index | A monthly price index designed to measure changes in prices of goods sold in primary markets |
| Quantity Index | An index designed to measure changes in quantities over time |
| Weighted Aggregate Price Index | A composite price index in which the prices of the items in the composite are weighted by their relative importance |
| Addition Law | A probability law used to compute the probability of the union of two events. It is P(a ∙ B) = P(a) + P(B) − P(a ∩ B). For mutually exclusive events, P(a ∩ B) = 0; in this case the addition law reduces to P(a ∙ B) = P(a) + P(B) |
| Basic Requirements for Assigning Probabilities | Two requirements that restrict the man- ner in which probability assignments can be made: (1) for each experimental outcome Ei we must have 0 ≤ P(Ei) ≤ 1; (2) considering all experimental outcomes, we must have P(E1) + P(E2) + . . . + P(En) = 1.0. |
| Bayes' Theorem | A method used to compute posterior probabilities |
| Classical Method | A method of assigning probabilities that is appropriate when all the experimental outcomes are equally likely |
| Combination | In an experiment we may be interested in determining the number of ways n objects may be selected from among n objects without regard to the order in which the n objects are selected |
| Complement of A | The event consisting of all sample points that are not in a |
| Conditional Probability | The probability of an event given that another event already occurred. The conditional probability of a given B is P(a ∣ B) = P(a ∩ B)/P(B). |
| Event | A collection of sample points |
| Experiment | A process that generates well-defined outcomes |
| Independent Events | Two events a and B where P(a ∣ B) = P(a) or P(B ∣ a) = P(B); that is, the events have no influence on each other |
| Intersection of A and B | The event containing the sample points belonging to both a and B. The intersection is denoted a ∩ B. |
| Joint Probability | The probability of two events both occurring; that is, the probability of the intersection of two events |
| Marginal Probability | The probability of an event given that another event already occurred. The conditional probability of a given B is P(a ∣ B) = P(a ∩ B)/P(B) |
| Multiple-Step Experiment | An experiment that can be described as a sequence of steps. If a multiple-step experiment has k steps with n1 possible outcomes on the first step, n2 possible outcomes on the second step, and so on |
| Multiplication Law | A probability law used to compute the probability of the intersection of two events. It is P(a ∩ B) = P(B)P(a ∣ B) or P(a ∩ B) = P(a)P(B ∣ a). For independent events it reduces to P(a ∩ B) = P(a)P(B) |
| Mutually Exclusive Events | Events that have no sample points in common; that is, a ∩ B is empty and P(a ∩ B) = 0. |
| Permutation | In an experiment we may be interested in determining the number of ways n objects may be selected from among n objects when the order in which the n objects are selected is important. |
| Posterior Probabilities | Revised probabilities of events based on additional information |
| Prior Probabilities | Initial estimates of the probabilities of events. |
| Probability | A numerical measure of the likelihood that an event will occur |
| Relative Frequency Method | A method of assigning probabilities that is appropriate when data are available to estimate the proportion of the time the experimental outcome will occur if the experiment is repeated a large number of times |
| Sample Point | The set of all experimental outcomes. |
| Subjective Method | A method of assigning probabilities on the basis of judgment |
| Tree Diagram | A graphical representation that helps in visualizing a multiple-step experiment |
| Union of A and B | The event containing all sample points belonging to a or B or both. The union is denoted a ∙ B |
| Venn Diagram | A graphical representation for showing symbolically the sample space and operations involving events in which the sample space is represented by a rectangle and events are represented as circles within the sample space |
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Faith64
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