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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. 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.






2. 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.






3. Some commonly used symbols for population parameters






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






5. To find the median value of a set of numbers: Arrange the numbers in numerical order. Locate the two middle numbers in the list. Find the average of those two middle values.






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






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






8. The objects described by a set of data: person (animal) - place - and - thing. (SUBJECTS)






9. 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.






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






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






12. Is the result of applying a statistical algorithm to a data set. It can also be described as an observable random variable.






13. 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






14. Failing to reject a false null hypothesis.






15. Any specific experimental condition applied to the subjects






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






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






18. Is the set of possible outcomes of an experiment. For example - the sample space for rolling a six-sided die will be {1 - 2 - 3 - 4 - 5 - 6}.






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






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






21. 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.






22. Is the study of the collection - organization - analysis - and interpretation of data. It deals with all aspects of this - including the planning of data collection in terms of the design of surveys and experiments.






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






24. 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






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






27. 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






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






29. 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.






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






31. A subjective estimate of probability.






32. 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.






33. A group of individuals sharing some common features that might affect the treatment.






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






35. 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






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






37. A numerical measure that describes an aspect of a sample.






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






39. 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.






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






41. Probability of rejecting a true null hypothesis.






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






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






44. Another name for elementary event.






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






47. 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






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






49. 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






50. 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.