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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. Are two related but separate academic disciplines. Statistical analysis often uses probability distributions - and the two topics are often studied together. However - probability theory contains much that is of mostly of mathematical interest and no






2. The result of a Bayesian analysis that encapsulates the combination of prior beliefs or information with observed data






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






4. Is a sample and the associated data points.






5. Describes the spread in the values of the sample statistic when many samples are taken.






6. A numerical measure that assesses the strength of a linear relationship between two variables.






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






8. Error also refers to the extent to which individual observations in a sample differ from a central value - such as






9. 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.






10. (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






11. Is inference about a population from a random sample drawn from it or - more generally - about a random process from its observed behavior during a finite period of time.






12. S^2






13. Is the exact middle value of a set of numbers Arrange the numbers in numerical order. Find the value in the middle of the list.






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






15. Failing to reject a false null hypothesis.






16. 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






17. Gives the probability distribution for a continuous random variable.






18. Is that part of a population which is actually observed.






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






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






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






22. ?r






23. Interpretation of statistical information in that the assumption is that whatever is proposed as a cause has no effect on the variable being measured can often involve the development of a






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






25. Can be a population parameter - a distribution parameter - an unobserved parameter (with different shades of meaning). In statistics - this is often a quantity to be estimated.

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26. In Bayesian inference - this represents prior beliefs or other information that is available before new data or observations are taken into account.






27. Is the function that gives the probability distribution of a random variable. It cannot be negative - and its integral on the probability space is equal to 1.






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






29. Is a measure of the 'peakedness' of the probability distribution of a real-valued random variable. Higher kurtosis means more of the variance is due to infrequent extreme deviations - as opposed to frequent modestly sized deviations.






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






31. A pairwise independent collection of random variables is a set of random variables any two of which are independent.






32. Is the study of the collection - organization - analysis - and interpretation of data. It deals with all aspects of this - including the planning of data collection in terms of the design of surveys and experiments.






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






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






35. Another name for elementary event.






36. 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.






37. 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






38. A subjective estimate of probability.






39. 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}.






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






41. 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






42. 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






43. Is the probability of two events occurring together. The joint probability of A and B is written P(A and B) or P(A - B).






44. A variable that has an important effect on the response variable and the relationship among the variables in a study but is not one of the explanatory variables studied either because it is unknown or not measured.






45.






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






47. 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.






48. Are simply two different terms for the same thing. Add the given values






49. Any specific experimental condition applied to the subjects






50. Some commonly used symbols for sample statistics