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






2. 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






3. 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.






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






5. 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.






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






7. The probability of the observed value or something more extreme under the assumption that the null hypothesis is true.






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






9. 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.






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






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






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






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






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






15. Is the most commonly used measure of statistical dispersion. It is the square root of the variance - and is generally written s (sigma).






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






17. Used to reduce bias - this measure weights the more relevant information higher than less relevant info.






18. Is a measure of its statistical dispersion - indicating how far from the expected value its values typically are. The variance of random variable X is typically designated as - - or simply s2.






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






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






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






22. 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.






23. ?r






24.






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






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






27. (e.g. ? - b) are commonly used to denote unknown parameters (population parameters).






28. Any specific experimental condition applied to the subjects






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






30. (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.






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






32. 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.






33. Error also refers to the extent to which individual observations in a sample differ from a central value - such as






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






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






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






37. (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






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






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






40. Is data that can take only two values - usually represented by 0 and 1.






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






42. Probability of accepting a false null hypothesis.






43. 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).






44. Is a parameter that indexes a family of probability distributions.






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






46. Failing to reject a false null hypothesis.






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






48. A subjective estimate of probability.






49. 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






50. Another name for elementary event.