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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 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






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






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






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






5. 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






6. (e.g. ? - b) are commonly used to denote unknown parameters (population parameters).






7. Probability of rejecting a true null hypothesis.






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






9. Uses patterns in the sample data to draw inferences about the population represented - accounting for randomness. These inferences may take the form of: answering yes/no questions about the data (hypothesis testing) - estimating numerical characteris






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






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

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






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






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






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






16. 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.






17. 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.






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






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






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






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






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






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






24. Cov[X - Y] :






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






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






28. 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.






29. E[X] :






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






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






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






33. Of a group of numbers is the center point of all those number values.






34. 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).






35. 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.






36. Failing to reject a false null hypothesis.






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






38. 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






39. Where the null hypothesis is falsely rejected giving a 'false positive'.






40. 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






41. Another name for elementary event.






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






43. 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.






44. 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'






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






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






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






48. (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.






49. 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






50. A list of individuals from which the sample is actually selected.







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