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






2. 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






3. 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






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






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






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






7. 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






8. ?r






9. Given two jointly distributed random variables X and Y - the conditional probability distribution of Y given X (written 'Y | X') is the probability distribution of Y when X is known to be a particular value.






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






11. 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






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






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






14. 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.






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






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






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






18. 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).






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






20. 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






21. Have no meaningful rank order among values.






22. 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.






23. 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.






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






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






26. 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






27. 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.






28. 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.






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






30. 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.






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






32. 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






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






34. The standard deviation of a sampling distribution.






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






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






37. 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.






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






39. Cov[X - Y] :






40. 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.






41. Samples are drawn from two different populations such that there is a matching of the first sample data drawn and a corresponding data value in the second sample data.






42. ?






43. 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.






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






45. (or expectation) of a random variable is the sum of the probability of each possible outcome of the experiment multiplied by its payoff ('value'). Thus - it represents the average amount one 'expects' to win per bet if bets with identical odds are re






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






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






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






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






50. (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