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






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






3. 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






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






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






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






7. 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'






8. ?r






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






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






11. E[X] :






12. (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






13. Rejecting a true null hypothesis.






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






15. 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






16. 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.






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






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






19. 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.






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






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






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






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






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






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






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






27. 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).






28. Have meaningful distances between measurements defined - but the zero value is arbitrary (as in the case with longitude and temperature measurements in Celsius or Fahrenheit)






29. 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






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






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






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






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






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






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






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






37. 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.






38. 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






39. Is a function that gives the probability of all elements in a given space: see List of probability distributions






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






41. 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






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






43. Any specific experimental condition applied to the subjects






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






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

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






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






48. 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.






49. 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.






50. Planning the research - including finding the number of replicates of the study - using the following information: preliminary estimates regarding the size of treatment effects - alternative hypotheses - and the estimated experimental variability. Co