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CLEP General Mathematics: Probability And Statistics

Subjects : clep, math
Instructions:
  • Answer 50 questions in 15 minutes.
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  • Match each statement with the correct term.
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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 set of entities about which statistical inferences are to be drawn - often based on random sampling. One can also talk about a population of measurements or values.






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






3. Involves taking measurements of the system under study - manipulating the system - and then taking additional measurements using the same procedure to determine if the manipulation has modified the values of the measurements.






4. 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.






5. (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






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






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






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






9. 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






10. 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






11. 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.






12. Is a measure of the asymmetry of the probability distribution of a real-valued random variable. Roughly speaking - a distribution has positive skew (right-skewed) if the higher tail is longer and negative skew (left-skewed) if the lower tail is longe






13. 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






14. 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






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






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






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

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18. 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.






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






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






21. Is often denoted by placing a caret over the corresponding symbol - e.g. - pronounced 'theta hat'.






22. Cov[X - Y] :






23. Working from a null hypothesis two basic forms of error are recognized:






24. A subjective estimate of probability.






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






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






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






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






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






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






31. 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






32. 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






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






34. ?r






35. A data value that falls outside the overall pattern of the graph.






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






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






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






39. 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.






40. ?






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






42. 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).






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






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






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






46. Summarize the population data by describing what was observed in the sample numerically or graphically. Numerical descriptors include mean and standard deviation for continuous data types (like heights or weights) - while frequency and percentage are






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






48. The proportion of the explained variation by a linear regression model in the total variation.






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






50. Some commonly used symbols for population parameters