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






2. A subjective estimate of probability.






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






4. A variable describes an individual by placing the individual into a category or a group.






5. Any specific experimental condition applied to the subjects






6. 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






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






8. Is used to describe probability in a continuous probability distribution. For example - you can't say that the probability of a man being six feet tall is 20% - but you can say he has 20% of chances of being between five and six feet tall. Probabilit






9.






10. Patterns in the data may be modeled in a way that accounts for randomness and uncertainty in the observations - and are then used for drawing inferences about the process or population being studied; this is called






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






12. 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






13. Is the probability distribution - under repeated sampling of the population - of a given statistic.






14. Is a measure of the asymmetry of the probability distribution of a real-valued random variable. Roughly speaking - a distribution has positive skew (right-skewed) if the higher tail is longer and negative skew (left-skewed) if the lower tail is longe






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






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






17. 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






18. 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






19. Probability of accepting a false null hypothesis.






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






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






22. Failing to reject a false null hypothesis.






23. Another name for elementary event.






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






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

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






27. 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.






28. 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.






29. (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






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






31. 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






32. 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.






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






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






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






36. 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.






37. ?r






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






39. Is a typed measurement - it can be a boolean value - a real number - a vector (in which case it's also called a data vector) - etc.






40. 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






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






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






43. 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.






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






45. Describes the spread in the values of the sample statistic when many samples are taken.






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






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






48. 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






49. 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.






50. 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







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