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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. 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






2. Many statistical methods seek to minimize the mean-squared error - and these are called






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






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






5. Have meaningful distances between measurements defined - but the zero value is arbitrary (as in the case with longitude and temperature measurements in Celsius or Fahrenheit)






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






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






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






9. A measurement such that the random error is small






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






11. Failing to reject a false null hypothesis.






12. Cov[X - Y] :






13. Probability of rejecting a true null hypothesis.






14. Is the length of the smallest interval which contains all the data.






15. 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






16. 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.






17. 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






18. 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.






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

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






21. The standard deviation of a sampling distribution.






22. 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.






23. The proportion of the explained variation by a linear regression model in the total variation.






24. 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.






25. In Bayesian inference - this represents prior beliefs or other information that is available before new data or observations are taken into account.






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






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






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






29. A numerical measure that describes an aspect of a population.






30. Is data arising from counting that can take only non-negative integer values.






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






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






33. 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






34. 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.






35. ?






36. 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).






37.






38. Statistics involve methods of organizing - picturing - and summarizing information from samples or population.






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






40. 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.






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






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. 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.






44. 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.






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






46. Uses patterns in the sample data to draw inferences about the population represented - accounting for randomness. These inferences may take the form of: answering yes/no questions about the data (hypothesis testing) - estimating numerical characteris






47. Any specific experimental condition applied to the subjects






48. ?r






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






50. 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.






Can you answer 50 questions in 15 minutes?



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