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






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






3. Is a sample and the associated data points.






4. Some commonly used symbols for population parameters






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






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






7.






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






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






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






11. A list of individuals from which the sample is actually selected.






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






13. 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).






14. In the long run - as the sample size increases - the relative frequencies of outcomes approach to the theoretical probability.






15. (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






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






17. 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






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






19. A collection of events is mutually independent if for any subset of the collection - the joint probability of all events occurring is equal to the product of the joint probabilities of the individual events. Think of the result of a series of coin-fl






20. The standard deviation of a sampling distribution.






21. S^2






22. Any specific experimental condition applied to the subjects






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






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






25. 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






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






27. Probability of accepting a false null hypothesis.






28. (or expectation) of a random variable is the sum of the probability of each possible outcome of the experiment multiplied by its payoff ('value'). Thus - it represents the average amount one 'expects' to win per bet if bets with identical odds are re






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






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






31. 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.






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






33. 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.






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






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






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






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






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






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






40. Failing to reject a false null hypothesis.






41. 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.






42. 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.






43. 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'






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






45. Are two related but separate academic disciplines. Statistical analysis often uses probability distributions - and the two topics are often studied together. However - probability theory contains much that is of mostly of mathematical interest and no






46. 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.






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






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






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






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.