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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. 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.






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






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






4. 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






5. 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}.






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






7. 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






8. 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






9. Is one that explores the correlation between smoking and lung cancer. This type of study typically uses a survey to collect observations about the area of interest and then performs statistical analysis. In this case - the researchers would collect o






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






11. 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'






12. Is a function that gives the probability of all elements in a given space: see List of probability distributions






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






14. (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






15. 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.






16. 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






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






18. Changes over time that show a regular periodicity in the data where regular means over a fixed interval; the time between repetitions is called the period.






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






20. 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






21. Is that part of a population which is actually observed.






22. Have no meaningful rank order among values.






23. Is data that can take only two values - usually represented by 0 and 1.






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. Rejecting a true null hypothesis.






26. 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.






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






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






29. Var[X] :






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






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






32. 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






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






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






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






36. 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






37. 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






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






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






40. 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.






41. 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.






42. Some commonly used symbols for sample statistics






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






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






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






46. 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.






47. 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.






48. 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).






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






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.