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






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






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






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






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






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






7.






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






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






10. Planning the research - including finding the number of replicates of the study - using the following information: preliminary estimates regarding the size of treatment effects - alternative hypotheses - and the estimated experimental variability. Co






11. 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






12. 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






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






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






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






17. Failing to reject a false null hypothesis.






18. 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.






19. Probability of rejecting a true null hypothesis.






20. 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.






21. A measurement such that the random error is small






22. (or just likelihood) is a conditional probability function considered a function of its second argument with its first argument held fixed. For example - imagine pulling a numbered ball with the number k from a bag of n balls - numbered 1 to n. Then






23. 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






24. Var[X] :






25. Probability of accepting a false null hypothesis.






26. The result of a Bayesian analysis that encapsulates the combination of prior beliefs or information with observed data






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






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






29. 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).






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






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






32. 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.






33. 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)






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






35. 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.






36. S^2






37. 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.






38. Any specific experimental condition applied to the subjects






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






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






41. 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






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






43. Can be a population parameter - a distribution parameter - an unobserved parameter (with different shades of meaning). In statistics - this is often a quantity to be estimated.

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






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






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






47. Have no meaningful rank order among values.






48. ?






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






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