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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 list of individuals from which the sample is actually selected.






2. 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.






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






4. 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.






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






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






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






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






9. 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






10. 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.






11. 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.






12. Some commonly used symbols for sample statistics






13. Probability of accepting a false null hypothesis.






14. Occurs when a subject receives no treatment - but (incorrectly) believes he or she is in fact receiving treatment and responds favorably.






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






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






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






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






19. 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.






20. The errors - or difference between the estimated response y^i and the actual measured response yi - collectively






21. Var[X] :






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






24. 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.






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






26. Is a sample space over which a probability measure has been defined.






27. Any specific experimental condition applied to the subjects






28. Have no meaningful rank order among values.






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






30. Are written in corresponding lower case letters. For example x1 - x2 - ... - xn could be a sample corresponding to the random variable X.






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






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






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






34. Interpretation of statistical information in that the assumption is that whatever is proposed as a cause has no effect on the variable being measured can often involve the development of a






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






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






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






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






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






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






42. 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






43. 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.






44. (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






45. Some commonly used symbols for population parameters






46. A variable that has an important effect on the response variable and the relationship among the variables in a study but is not one of the explanatory variables studied either because it is unknown or not measured.






47. 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.






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






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






50. 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