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CLEP General Mathematics: Probability And Statistics

Subjects : clep, math
Instructions:
  • Answer 50 questions in 15 minutes.
  • If you are not ready to take this test, you can study here.
  • 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. A numerical facsimilie or representation of a real-world phenomenon.






2. 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.






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






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

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5. The proportion of the explained variation by a linear regression model in the total variation.






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






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






8. 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






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






10. 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






11. A consistent - repeated deviation of the sample statistic from the population parameter in the same direction when many samples are taken.






12. A common goal for a statistical research project is to investigate causality - and in particular to draw a conclusion on the effect of changes in the values of predictors or independent variables on dependent variables or response.






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






14. Another name for elementary event.






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






16. To prove the guiding theory further - these predictions are tested as well - as part of the scientific method. If the inference holds true - then the descriptive statistics of the new data increase the soundness of that






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






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






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






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






21.






22. Is inference about a population from a random sample drawn from it or - more generally - about a random process from its observed behavior during a finite period of time.






23. A subjective estimate of probability.






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






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






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






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






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






29. 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.






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






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






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






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






34. 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.






35. Var[X] :






36. Cov[X - Y] :






37. 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.






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






39. Is a sample and the associated data points.






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






41. 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.






42. 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.






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






44. Some commonly used symbols for population parameters






45. 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






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






48. ?






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. 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.