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






2. 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






3. 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.






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






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






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






7. Probability of accepting a false null hypothesis.






8. 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.






9. 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.






10. Var[X] :






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






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






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






14. 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






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






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






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






18. Is one that explores the correlation between smoking and lung cancer. This type of study typically uses a survey to collect observations about the area of interest and then performs statistical analysis. In this case - the researchers would collect o






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






20. Failing to reject a false null hypothesis.






21. A sample selected in such a way that each individual is equally likely to be selected as well as any group of size n is equally likely to be selected.






22. Cov[X - Y] :






23. 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.






24. Rejecting a true null hypothesis.






25. 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






26. 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.






27. 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.






28. 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






29. To find the median value of a set of numbers: Arrange the numbers in numerical order. Locate the two middle numbers in the list. Find the average of those two middle values.






30. Is the probability of some event A - assuming event B. Conditional probability is written P(A|B) - and is read 'the probability of A - given B'






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






32. Is used to describe probability in a continuous probability distribution. For example - you can't say that the probability of a man being six feet tall is 20% - but you can say he has 20% of chances of being between five and six feet tall. Probabilit






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






34. 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).






35. (also called statistical variability) is a measure of how diverse some data is. It can be expressed by the variance or the standard deviation.






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






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






38. 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.






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






40. 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






41. Probability of rejecting a true null hypothesis.






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






43. 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






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






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






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






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






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