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






2. 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






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






4. To find the average - or arithmetic mean - of a set of numbers:






5. 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.






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






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






8. 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.






9. Also called correlation coefficient - is a numeric measure of the strength of linear relationship between two random variables (one can use it to quantify - for example - how shoe size and height are correlated in the population). An example is the P






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






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






12. A consistent - repeated deviation of the sample statistic from the population parameter in the same direction when many samples are taken.






13. E[X] :






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






15. Is a function that gives the probability of all elements in a given space: see List of probability distributions






16. A list of individuals from which the sample is actually selected.






17. In number theory - scatter plots of data generated by a distribution function may be transformed with familiar tools used in statistics to reveal underlying patterns - which may then lead to






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






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






20. 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.






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






22. Are simply two different terms for the same thing. Add the given values






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






24. Another name for elementary event.






25. 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).






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






27. 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.






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






29. Any specific experimental condition applied to the subjects






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






31. (or atomic event) is an event with only one element. For example - when pulling a card out of a deck - 'getting the jack of spades' is an elementary event - while 'getting a king or an ace' is not.






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






33. Is the result of applying a statistical algorithm to a data set. It can also be described as an observable random variable.






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






35. Is the most commonly used measure of statistical dispersion. It is the square root of the variance - and is generally written s (sigma).






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






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






38. 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






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






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






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






42. 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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43. The standard deviation of a sampling distribution.






44. Some commonly used symbols for sample statistics






45. 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






46. (pdfs) and probability mass functions are denoted by lower case letters - e.g. f(x).






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






48. 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






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






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