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






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






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






4. To find the median value of a set of numbers: Arrange the numbers in numerical order. Locate the two middle numbers in the list. Find the average of those two middle values.






5.






6. 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






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






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






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






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






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






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






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






14. Var[X] :






15. 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






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






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






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

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






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






21. Is used in 'mathematical statistics' (alternatively - 'statistical theory') to study the sampling distributions of sample statistics and - more generally - the properties of statistical procedures. The use of any statistical method is valid when the






22. There are four main levels of measurement used in statistics: Each of these have different degrees of usefulness in statistical research.






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






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






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






26. Cov[X - Y] :






27. 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.






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






29. Are usually written in upper case roman letters: X - Y - etc.






30. 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}.






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






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






33. 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






34. (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






35. 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.






36. Can be - for example - the possible outcomes of a dice roll (but it is not assigned a value). The distribution function of a random variable gives the probability of different results. We can also derive the mean and variance of a random variable.






37. When there is an even number of values...






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






39. In particular - the pdf of the standard normal distribution is denoted by






40. 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






41. 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.






42. Have no meaningful rank order among values.






43. Rejecting a true null hypothesis.






44. 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






45. 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.






46. 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.






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






48. Is the most commonly used measure of statistical dispersion. It is the square root of the variance - and is generally written s (sigma).






49. 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.






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






Can you answer 50 questions in 15 minutes?



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