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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. (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






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






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






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






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






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






8. 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.






9. Any specific experimental condition applied to the subjects






10. 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.






11. Cov[X - Y] :






12. ?r






13. A subjective estimate of probability.






14. (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






15. Some commonly used symbols for sample statistics






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






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






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






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






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






21. S^2






22.






23. 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).






24. Consists of a number of independent trials repeated under identical conditions. On each trial - there are two possible outcomes.






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






26. 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






27. 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.






28. 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






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






30. The probability of the observed value or something more extreme under the assumption that the null hypothesis is true.






31. Working from a null hypothesis two basic forms of error are recognized:






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






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






34. Is inference about a population from a random sample drawn from it or - more generally - about a random process from its observed behavior during a finite period of time.






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






36. 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






37. Two variables such that their effects on the response variable cannot be distinguished from each other.






38. 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.






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






40. 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.






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






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






43. 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






44. ?






45. 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






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






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






48. When there is an even number of values...






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






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