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CLEP General Mathematics: Probability And Statistics

Subjects : clep, math
Instructions:
  • Answer 50 questions in 15 minutes.
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  • Match each statement with the correct term.
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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 subjective estimate of probability.






2. 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.






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






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






5. 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






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






7. S^2






8. 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






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






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






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






12. 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






13. A data value that falls outside the overall pattern of the graph.






14. Another name for elementary event.






15. Given two jointly distributed random variables X and Y - the conditional probability distribution of Y given X (written 'Y | X') is the probability distribution of Y when X is known to be a particular value.






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






17. Any specific experimental condition applied to the subjects






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






19. 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.






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






21. 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.






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






23. Have no meaningful rank order among values.






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






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






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






27. 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






28. Two events are independent if the outcome of one does not affect that of the other (for example - getting a 1 on one die roll does not affect the probability of getting a 1 on a second roll). Similarly - when we assert that two random variables are i






29. Rejecting a true null hypothesis.






30. 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.






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






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






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






34. Probability of rejecting a true null hypothesis.






35. 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).






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






37. 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.






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






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






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






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






42. 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.






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






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






45. Design of experiments - using blocking to reduce the influence of confounding variables - and randomized assignment of treatments to subjects to allow unbiased estimates of treatment effects and experimental error. At this stage - the experimenters a






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






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

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48. 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.






49. 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.






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