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






2. 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.






3. 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






4. 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.






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






6. Is used to describe probability in a continuous probability distribution. For example - you can't say that the probability of a man being six feet tall is 20% - but you can say he has 20% of chances of being between five and six feet tall. Probabilit






7. Var[X] :






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






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






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






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






12. 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.






13. ?






14. 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






15. The standard deviation of a sampling distribution.






16. 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.






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






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






19. Also called correlation coefficient - is a numeric measure of the strength of linear relationship between two random variables (one can use it to quantify - for example - how shoe size and height are correlated in the population). An example is the P






20. (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






21. 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.






22. 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.






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






24. 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






25. Failing to reject a false null hypothesis.






26. 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.






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






28. Cov[X - Y] :






29. 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.






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






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






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






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






34. S^2






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






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






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






38. (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.






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






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






41. A group of individuals sharing some common features that might affect the treatment.






42. A measurement such that the random error is small






43. Is the probability of two events occurring together. The joint probability of A and B is written P(A and B) or P(A - B).






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






45. 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






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






47. 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






48. A variable has a value or numerical measurement for which operations such as addition or averaging make sense.






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






50. 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).