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






2. 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.






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






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. 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






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






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






8. 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.






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






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






11. 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.






12. 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






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






14. 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).






15. Is a sample and the associated data points.






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






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






18. 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






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






20. 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.






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






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






23. Samples are drawn from two different populations such that the sample data drawn from one population is completely unrelated to the selection of sample data from the other population.






24. (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






25. 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.






26. Have no meaningful rank order among values.






27. 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.






28. A variable that has an important effect on the response variable and the relationship among the variables in a study but is not one of the explanatory variables studied either because it is unknown or not measured.






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






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






31. 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.






32. Is data arising from counting that can take only non-negative integer values.






33. 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.






34. Var[X] :






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






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






37. 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.






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






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






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






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






42. Some commonly used symbols for sample statistics






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






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






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






46. 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






47. 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






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






49. Describes the spread in the values of the sample statistic when many samples are taken.






50. 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






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