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CLEP General Mathematics: Probability And Statistics

Subjects : clep, math
Instructions:
  • Answer 50 questions in 15 minutes.
  • If you are not ready to take this test, you can study here.
  • Match each statement with the correct term.
  • Don't refresh. All questions and answers are randomly picked and ordered every time you load a test.

This is a study tool. The 3 wrong answers for each question are randomly chosen from answers to other questions. So, you might find at times the answers obvious, but you will see it re-enforces your understanding as you take the test each time.
1. When info. in a contingency table is re-organized into more or less categories - relationships seen can change or reverse.


2. In the long run - as the sample size increases - the relative frequencies of outcomes approach to the theoretical probability.






3. (or expectation) of a random variable is the sum of the probability of each possible outcome of the experiment multiplied by its payoff ('value'). Thus - it represents the average amount one 'expects' to win per bet if bets with identical odds are re






4. A collection of events is mutually independent if for any subset of the collection - the joint probability of all events occurring is equal to the product of the joint probabilities of the individual events. Think of the result of a series of coin-fl






5. Consists of a number of independent trials repeated under identical conditions. On each trial - there are two possible outcomes.






6. Is data arising from counting that can take only non-negative integer values.






7. A numerical measure that describes an aspect of a sample.






8. Is the probability of some event A - assuming event B. Conditional probability is written P(A|B) - and is read 'the probability of A - given B'






9. Design of experiments - using blocking to reduce the influence of confounding variables - and randomized assignment of treatments to subjects to allow unbiased estimates of treatment effects and experimental error. At this stage - the experimenters a






10. Is the probability of an event - ignoring any information about other events. The marginal probability of A is written P(A). Contrast with conditional probability.






11. Is the result of applying a statistical algorithm to a data set. It can also be described as an observable random variable.






12. There are two major types of causal statistical studies: In both types of studies - the effect of differences of an independent variable (or variables) on the behavior of the dependent variable are observed. The difference between the two types lies






13. Cov[X - Y] :






14. Statistics involve methods of using information from a sample to draw conclusions regarding the population.






15. In number theory - scatter plots of data generated by a distribution function may be transformed with familiar tools used in statistics to reveal underlying patterns - which may then lead to






16. Because variables conforming only to nominal or ordinal measurements cannot be reasonably measured numerically - sometimes they are grouped together as






17. Ratio and interval measurements which can be either discrete or continuous - due to their numerical nature are grouped together as






18. A list of individuals from which the sample is actually selected.






19. A consistent - repeated deviation of the sample statistic from the population parameter in the same direction when many samples are taken.






20. The objects described by a set of data: person (animal) - place - and - thing. (SUBJECTS)






21. A sample selected in such a way that each individual is equally likely to be selected as well as any group of size n is equally likely to be selected.






22. Have no meaningful rank order among values.






23. (or atomic event) is an event with only one element. For example - when pulling a card out of a deck - 'getting the jack of spades' is an elementary event - while 'getting a king or an ace' is not.






24. To find the average - or arithmetic mean - of a set of numbers:






25. Used to reduce bias - this measure weights the more relevant information higher than less relevant info.






26. A measure that is relevant or appropriate as a representation of that property.






27. A scale that represents an ordinal scale such as looks on a scale from 1 to 10.






28. Performing the experiment following the experimental protocol and analyzing the data following the experimental protocol. 4. Further examining the data set in secondary analyses - to suggest new hypotheses for future study. 5. Documenting and present






29. The errors - or difference between the estimated response y^i and the actual measured response yi - collectively






30. The collection of all possible outcomes in an experiment.






31. A common goal for a statistical research project is to investigate causality - and in particular to draw a conclusion on the effect of changes in the values of predictors or independent variables on dependent variables or response.






32. Are written in corresponding lower case letters. For example x1 - x2 - ... - xn could be a sample corresponding to the random variable X.






33. Some commonly used symbols for sample statistics






34. Have imprecise differences between consecutive values - but have a meaningful order to those values






35. Is a typed measurement - it can be a boolean value - a real number - a vector (in which case it's also called a data vector) - etc.






36. A numerical facsimilie or representation of a real-world phenomenon.






37. A variable describes an individual by placing the individual into a category or a group.






38. Another name for elementary event.






39. Working from a null hypothesis two basic forms of error are recognized:






40. E[X] :






41. Is a set of entities about which statistical inferences are to be drawn - often based on random sampling. One can also talk about a population of measurements or values.






42. Is the set of possible outcomes of an experiment. For example - the sample space for rolling a six-sided die will be {1 - 2 - 3 - 4 - 5 - 6}.






43. When you have two or more competing models - choose the simpler of the two models.






44. (also called statistical variability) is a measure of how diverse some data is. It can be expressed by the variance or the standard deviation.






45. A group of individuals sharing some common features that might affect the treatment.






46. (or just likelihood) is a conditional probability function considered a function of its second argument with its first argument held fixed. For example - imagine pulling a numbered ball with the number k from a bag of n balls - numbered 1 to n. Then






47. Is a sample and the associated data points.






48. Given two random variables X and Y - the joint distribution of X and Y is the probability distribution of X and Y together.






49. Given two jointly distributed random variables X and Y - the conditional probability distribution of Y given X (written 'Y | X') is the probability distribution of Y when X is known to be a particular value.






50. Where the null hypothesis is falsely rejected giving a 'false positive'.