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






2. Is a measure of its statistical dispersion - indicating how far from the expected value its values typically are. The variance of random variable X is typically designated as - - or simply s2.






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






4. Var[X] :






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






6. 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.






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






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






9. Is a function of the known data that is used to estimate an unknown parameter; an estimate is the result from the actual application of the function to a particular set of data. The mean can be used as an estimator.






10. 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






11. A measurement such that the random error is small






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






13. The probability of the observed value or something more extreme under the assumption that the null hypothesis is true.






14. 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.






15. Any specific experimental condition applied to the subjects






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






17. Another name for elementary event.






18. (pdfs) and probability mass functions are denoted by lower case letters - e.g. f(x).






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






20. Have no meaningful rank order among values.






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






22. Cov[X - Y] :






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






24. Is a parameter that indexes a family of probability distributions.






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






26. 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






27. 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






28. Probability of accepting a false null hypothesis.






29. 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






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






31. 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.






32. 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}.






33. Failing to reject a false null hypothesis.






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






35. 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.






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






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






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






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






40. (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






41. 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






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






43. 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






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






45. 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.






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






47. 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






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






49. 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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50. Is a measure of the asymmetry of the probability distribution of a real-valued random variable. Roughly speaking - a distribution has positive skew (right-skewed) if the higher tail is longer and negative skew (left-skewed) if the lower tail is longe