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CLEP General Mathematics: Probability And Statistics

Subjects : clep, math
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  • 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. Some commonly used symbols for sample statistics






2. The standard deviation of a sampling distribution.






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






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






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






6. S^2






7. Have no meaningful rank order among values.






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






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






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






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






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






13. 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






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






15. Var[X] :






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






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






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






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






20. Have meaningful distances between measurements defined - but the zero value is arbitrary (as in the case with longitude and temperature measurements in Celsius or Fahrenheit)






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






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






23. 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}.






24. 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.






25. Rejecting a true null hypothesis.






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






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






28. Some commonly used symbols for population parameters






29. 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






30. 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






31. (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.






32. 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.






33. 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






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






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






36. 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.






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






38. 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.






39. Is a sample and the associated data points.






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






41. Are simply two different terms for the same thing. Add the given values






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






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






44. Planning the research - including finding the number of replicates of the study - using the following information: preliminary estimates regarding the size of treatment effects - alternative hypotheses - and the estimated experimental variability. Co






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






46. 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.






47. Any specific experimental condition applied to the subjects






48. 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






49. 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.






50. Is the study of the collection - organization - analysis - and interpretation of data. It deals with all aspects of this - including the planning of data collection in terms of the design of surveys and experiments.







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