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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. Statistics involve methods of using information from a sample to draw conclusions regarding the population.






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






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






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






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






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






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






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






9. 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.






10. Any specific experimental condition applied to the subjects






11. Design of experiments - using blocking to reduce the influence of confounding variables - and randomized assignment of treatments to subjects to allow unbiased estimates of treatment effects and experimental error. At this stage - the experimenters a






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






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






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






16. Is a sample and the associated data points.






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






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






19. 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






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






21. 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.






22. 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






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






24. 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






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






26. A scale that represents an ordinal scale such as looks on a scale from 1 to 10.






27. ?






28. Probability of rejecting a true null hypothesis.






29. 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.






30. Some commonly used symbols for population parameters






31. Performing the experiment following the experimental protocol and analyzing the data following the experimental protocol. 4. Further examining the data set in secondary analyses - to suggest new hypotheses for future study. 5. Documenting and present






32. 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.






33. There are four main levels of measurement used in statistics: Each of these have different degrees of usefulness in statistical research.






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






35. There are two major types of causal statistical studies: In both types of studies - the effect of differences of an independent variable (or variables) on the behavior of the dependent variable are observed. The difference between the two types lies






36. 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.






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






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






39. Some commonly used symbols for sample statistics






40. (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.






41.






42. The standard deviation of a sampling distribution.






43. 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.






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






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






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






48. 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.






49. 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.






50. Is a subset of the sample space - to which a probability can be assigned. For example - on rolling a die - 'getting a five or a six' is an event (with a probability of one third if the die is fair).