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CLEP General Mathematics: Probability And Statistics

Subjects : clep, math
Instructions:
  • Answer 50 questions in 15 minutes.
  • If you are not ready to take this test, you can study here.
  • 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. (or multivariate random variable) is a vector whose components are random variables on the same probability space.






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

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3. 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.






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






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






6. A list of individuals from which the sample is actually selected.






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






8. Data are gathered and correlations between predictors and response are investigated.






9. 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.






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






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






12. 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






13. 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






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






15. E[X] :






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






17. 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.






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






19. The probability of correctly detecting a false null hypothesis.






20. Samples are drawn from two different populations such that there is a matching of the first sample data drawn and a corresponding data value in the second sample data.






21. S^2






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






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






24. 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.






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






26. Any specific experimental condition applied to the subjects






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






28. 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






29. 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






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






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






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






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






34. Failing to reject a false null hypothesis.






35. Var[X] :






36. Is the probability of an event - ignoring any information about other events. The marginal probability of A is written P(A). Contrast with conditional probability.






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






38. ?






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






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






41. 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.






42. 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.






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






44. Planning the research - including finding the number of replicates of the study - using the following information: preliminary estimates regarding the size of treatment effects - alternative hypotheses - and the estimated experimental variability. Co






45. Have both a meaningful zero value and the distances between different measurements defined; they provide the greatest flexibility in statistical methods that can be used for analyzing the data






46. A subjective estimate of probability.






47. 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.






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






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






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