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






2. (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






3. A variable has a value or numerical measurement for which operations such as addition or averaging make sense.






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






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






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






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

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8. 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






9. ?






10. Because variables conforming only to nominal or ordinal measurements cannot be reasonably measured numerically - sometimes they are grouped together as






11. Probability of accepting a false null hypothesis.






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






13. Is a measure of the asymmetry of the probability distribution of a real-valued random variable. Roughly speaking - a distribution has positive skew (right-skewed) if the higher tail is longer and negative skew (left-skewed) if the lower tail is longe






14. 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)






15. 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






16. 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






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






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






19. 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.






20. Is often denoted by placing a caret over the corresponding symbol - e.g. - pronounced 'theta hat'.






21. 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.






22. The standard deviation of a sampling distribution.






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






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






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






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






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






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






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






30. 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.






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






32. 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.






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






34. Have no meaningful rank order among values.






35. 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.






36. Rejecting a true null hypothesis.






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






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






40. A measurement such that the random error is small






41. 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






42. Have both a meaningful zero value and the distances between different measurements defined; they provide the greatest flexibility in statistical methods that can be used for analyzing the data






43. 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.






44. S^2






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






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






47. 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.






48. 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.






49. Changes over time that show a regular periodicity in the data where regular means over a fixed interval; the time between repetitions is called the period.






50. 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.