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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.
  • Don't refresh. All questions and answers are randomly picked and ordered every time you load a test.

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 the probability of two events occurring together. The joint probability of A and B is written P(A and B) or P(A - B).






2. 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.






3. A collection of events is mutually independent if for any subset of the collection - the joint probability of all events occurring is equal to the product of the joint probabilities of the individual events. Think of the result of a series of coin-fl






4. 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






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






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






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






8. 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.






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. Another name for elementary event.






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






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






13. 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.






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






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






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






17. 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.






18. 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






19. Probability of accepting a false null hypothesis.






20. (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






21. Consists of a number of independent trials repeated under identical conditions. On each trial - there are two possible outcomes.






22. 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.






23. Statistical methods can be used for summarizing or describing a collection of data; this is called






24. 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.






25. Is a sample and the associated data points.






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






27. 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






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






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






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






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






32. 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






33. Rejecting a true null hypothesis.






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






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






36. Failing to reject a false null hypothesis.






37. 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






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






39. Statistics involve methods of organizing - picturing - and summarizing information from samples or population.






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






41. 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.






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






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






44. 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






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






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






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

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48. 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.






49. (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






50. 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.