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






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






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






4. To find the average - or arithmetic mean - of a set of numbers:






5. Probability of accepting a false null hypothesis.






6. 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






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






8. Can refer either to a sample not being representative of the population - or to the difference between the expected value of an estimator and the true value.






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






10. 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






11. 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.






12. A measurement such that the random error is small






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






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






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






16. (or multivariate random variable) is a vector whose components are random variables on the same probability space.






17. A numerical facsimilie or representation of a real-world phenomenon.






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






19. 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.






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






21. (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






22. 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.






23. (or atomic event) is an event with only one element. For example - when pulling a card out of a deck - 'getting the jack of spades' is an elementary event - while 'getting a king or an ace' is not.






24. 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.






25. Samples are drawn from two different populations such that the sample data drawn from one population is completely unrelated to the selection of sample data from the other population.






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






27. The standard deviation of a sampling distribution.






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






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






30. Is a sample and the associated data points.






31. 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






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






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






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






35. 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






36. Cov[X - Y] :






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






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






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






40. Is a process of selecting observations to obtain knowledge about a population. There are many methods to choose on which sample to do the observations.






41. Is the probability of some event A - assuming event B. Conditional probability is written P(A|B) - and is read 'the probability of A - given B'






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






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






44. Some commonly used symbols for population parameters






45. (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






46. ?






47. 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.


48. Another name for elementary event.






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






50. 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.