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






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






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






4. 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






5. A numerical measure that describes an aspect of a population.






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






7. 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.






8. 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






9. 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.






10. 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






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






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






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






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






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






16. 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.






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






18. 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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19. Samples are drawn from two different populations such that there is a matching of the first sample data drawn and a corresponding data value in the second sample data.






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






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






22. 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






23. 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






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






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

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






27. A measure that is relevant or appropriate as a representation of that property.






28. Some commonly used symbols for population parameters






29. Is a process of selecting observations to obtain knowledge about a population. There are many methods to choose on which sample to do the observations.






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






31. Is a sample and the associated data points.






32. 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






33. 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






34. 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.






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






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






37. 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.






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






39. (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.






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






41. 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.






42. Probability of accepting a false null hypothesis.






43. 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.






44. 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.






45. (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






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






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






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






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






50. The standard deviation of a sampling distribution.







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