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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 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






2. 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.






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






4. 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.






5. (pdfs) and probability mass functions are denoted by lower case letters - e.g. f(x).






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






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






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






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






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






11. Another name for elementary event.






12. 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.






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






14. A measurement such that the random error is small






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






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






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






19. 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






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






21. 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.






22. Patterns in the data may be modeled in a way that accounts for randomness and uncertainty in the observations - and are then used for drawing inferences about the process or population being studied; this is called






23. Is the exact middle value of a set of numbers Arrange the numbers in numerical order. Find the value in the middle of the list.






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






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






26. 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.






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






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






29. Some commonly used symbols for population parameters






30. Any specific experimental condition applied to the subjects






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






32. S^2






33. 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)






34. Is data arising from counting that can take only non-negative integer values.






35. 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.






36. Probability of accepting a false null hypothesis.






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






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






39. (or expectation) of a random variable is the sum of the probability of each possible outcome of the experiment multiplied by its payoff ('value'). Thus - it represents the average amount one 'expects' to win per bet if bets with identical odds are re






40. E[X] :






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






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






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






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






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






46. Ratio and interval measurements which can be either discrete or continuous - due to their numerical nature are grouped together as






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






48.






49. Failing to reject a false null hypothesis.






50. 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.