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






2. (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.






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






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






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






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






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






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






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






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






11. 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.






12. Are usually written with upper case calligraphic (e.g. F for the set of sets on which we define the probability P)






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






14. 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.






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






16. 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






17. 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.






18.






19. A subjective estimate of probability.






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






21. S^2






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






23. Var[X] :






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






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






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






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






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






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






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






32. 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






33. There are two major types of causal statistical studies: In both types of studies - the effect of differences of an independent variable (or variables) on the behavior of the dependent variable are observed. The difference between the two types lies






34. Are simply two different terms for the same thing. Add the given values






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






36. 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






37. 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).






38. Cov[X - Y] :






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






40. 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.






41. ?r






42. Statistical methods can be used for summarizing or describing a collection of data; this is called






43. Two variables such that their effects on the response variable cannot be distinguished from each other.






44. Is the length of the smallest interval which contains all the data.






45. The standard deviation of a sampling distribution.






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






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






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






49. 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






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