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CLEP General Mathematics: Probability And Statistics

Subjects : clep, math
Instructions:
  • Answer 50 questions in 15 minutes.
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  • Match each statement with the correct term.
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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. Patterns in the data may be modeled in a way that accounts for randomness and uncertainty in the observations - and are then used for drawing inferences about the process or population being studied; this is called






2. Is a subset of the sample space - to which a probability can be assigned. For example - on rolling a die - 'getting a five or a six' is an event (with a probability of one third if the die is fair).






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






4. The standard deviation of a sampling distribution.






5. Is one that explores the correlation between smoking and lung cancer. This type of study typically uses a survey to collect observations about the area of interest and then performs statistical analysis. In this case - the researchers would collect o






6. Many statistical methods seek to minimize the mean-squared error - and these are called






7. Can refer either to a sample not being representative of the population - or to the difference between the expected value of an estimator and the true value.






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






9. Are usually written with upper case calligraphic (e.g. F for the set of sets on which we define the probability P)






10. Of a group of numbers is the center point of all those number values.






11. Statistical methods can be used for summarizing or describing a collection of data; this is called






12. Gives the probability of events in a probability space.






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






14. A variable has a value or numerical measurement for which operations such as addition or averaging make sense.






15. Is its expected value. The mean (or sample mean of a data set is just the average value.






16. 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.






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






18. (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.






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






20. Is denoted by - pronounced 'x bar'.






21.






22. (cdfs) are denoted by upper case letters - e.g. F(x).






23. (e.g. ? - b) are commonly used to denote unknown parameters (population parameters).






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






25. Two events are independent if the outcome of one does not affect that of the other (for example - getting a 1 on one die roll does not affect the probability of getting a 1 on a second roll). Similarly - when we assert that two random variables are i






26. Is the probability distribution - under repeated sampling of the population - of a given statistic.






27. Two variables such that their effects on the response variable cannot be distinguished from each other.






28. 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'






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






30. 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.






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






32. Statistics involve methods of organizing - picturing - and summarizing information from samples or population.






33. Is used to describe probability in a continuous probability distribution. For example - you can't say that the probability of a man being six feet tall is 20% - but you can say he has 20% of chances of being between five and six feet tall. Probabilit






34. Uses patterns in the sample data to draw inferences about the population represented - accounting for randomness. These inferences may take the form of: answering yes/no questions about the data (hypothesis testing) - estimating numerical characteris






35. Is often denoted by placing a caret over the corresponding symbol - e.g. - pronounced 'theta hat'.






36. Rejecting a true null hypothesis.






37. A data value that falls outside the overall pattern of the graph.






38. A subjective estimate of probability.






39. When info. in a contingency table is re-organized into more or less categories - relationships seen can change or reverse.

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40. Is a function that gives the probability of all elements in a given space: see List of probability distributions






41. Summarize the population data by describing what was observed in the sample numerically or graphically. Numerical descriptors include mean and standard deviation for continuous data types (like heights or weights) - while frequency and percentage are






42. Samples are drawn from two different populations such that the sample data drawn from one population is completely unrelated to the selection of sample data from the other population.






43. Any specific experimental condition applied to the subjects






44. 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.






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






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






47. Long-term upward or downward movement over time.






48. A measurement such that the random error is small






49. 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.






50. Is the length of the smallest interval which contains all the data.







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