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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. Two events are independent if the outcome of one does not affect that of the other (for example - getting a 1 on one die roll does not affect the probability of getting a 1 on a second roll). Similarly - when we assert that two random variables are i






2. 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.






3. Another name for elementary event.






4. Is denoted by - pronounced 'x bar'.






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






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






7. (also called statistical variability) is a measure of how diverse some data is. It can be expressed by the variance or the standard deviation.






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






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






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






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






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






13. A subjective estimate of probability.






14. Failing to reject a false null hypothesis.






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






16. The standard deviation of a sampling distribution.






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






18. A measurement such that the random error is small






19. 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






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






21. 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.






22. 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






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






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






25. Is a typed measurement - it can be a boolean value - a real number - a vector (in which case it's also called a data vector) - etc.






26. 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.






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






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






29. 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.






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






31. (cdfs) are denoted by upper case letters - e.g. F(x).






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






33. Have no meaningful rank order among values.






34. 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.

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35. 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.






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






37. 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






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






39. 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.






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






41. 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






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






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

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44.






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






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






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






49. 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.






50. Gives the probability distribution for a continuous random variable.