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






2. Is the function that gives the probability distribution of a random variable. It cannot be negative - and its integral on the probability space is equal to 1.






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






4. 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.






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






6. ?r






7. 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






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






9. Any specific experimental condition applied to the subjects






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






11. In particular - the pdf of the standard normal distribution is denoted by






12. 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.






13. 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






14. 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.






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






16. 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.






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






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






19. Is the probability of two events occurring together. The joint probability of A and B is written P(A and B) or P(A - B).






20. 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.






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






22. S^2






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






24. 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.






25. Failing to reject a false null hypothesis.






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






27. 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.






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






29. A measurement such that the random error is small






30. 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)






31. Where the null hypothesis is falsely rejected giving a 'false positive'.






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


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






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






35. 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






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






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






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






39. ?






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






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






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






43. 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.






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






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






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. 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






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






49. 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.






50. 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).