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






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






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






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






5. (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






6. Describes a characteristic of an individual to be measured or observed.






7. ?r






8. Descriptive statistics and inferential statistics (a.k.a. - predictive statistics) together comprise






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






10. Occurs when a subject receives no treatment - but (incorrectly) believes he or she is in fact receiving treatment and responds favorably.






11. S^2






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






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






14. 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






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






16. To prove the guiding theory further - these predictions are tested as well - as part of the scientific method. If the inference holds true - then the descriptive statistics of the new data increase the soundness of that






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






18. 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.






19. 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).






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






21. 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






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






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






24. 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.






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






27. Have no meaningful rank order among values.






28. Where the null hypothesis fails to be rejected and an actual difference between populations is missed giving a 'false negative'.






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

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30. 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.






31. Some commonly used symbols for sample statistics






32. E[X] :






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






34. 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






35. (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






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






37. A numerical measure that describes an aspect of a population.






38. Var[X] :






39. The probability distribution of a sample statistic based on all the possible simple random samples of the same size from a population.






40. Is a sample space over which a probability measure has been defined.






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






42. ?






43. Is defined as the expected value of random variable (X -






44. 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.






45. Given two jointly distributed random variables X and Y - the marginal distribution of X is simply the probability distribution of X ignoring information about Y.






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






47. 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






48. Failing to reject a false null hypothesis.






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






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






Can you answer 50 questions in 15 minutes?



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