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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. Var[X] :






2. 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.






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






4. 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.






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






6. 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.






7. 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.






8. Have no meaningful rank order among values.






9. 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






10. 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






11. The standard deviation of a sampling distribution.






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






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






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






15. 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.






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






17. Failing to reject a false null hypothesis.






18. 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






19. Rejecting a true null hypothesis.






20. 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






21. Probability of rejecting a true null hypothesis.






22. 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






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






24. 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).






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






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






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






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






30. 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.






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






32. Is that part of a population which is actually observed.






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






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






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






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






37. When you have two or more competing models - choose the simpler of the two models.






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






39. S^2






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






41. Some commonly used symbols for population parameters






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






43. 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.






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






45. A numerical facsimilie or representation of a real-world phenomenon.






46. A sample selected in such a way that each individual is equally likely to be selected as well as any group of size n is equally likely to be selected.






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






48. A common goal for a statistical research project is to investigate causality - and in particular to draw a conclusion on the effect of changes in the values of predictors or independent variables on dependent variables or response.






49. 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






50. 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