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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. 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






2. 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.






3. Some commonly used symbols for population parameters






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






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






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






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






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






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






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






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






12. (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.






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






14. The standard deviation of a sampling distribution.






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. 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






17. Two events are independent if the outcome of one does not affect that of the other (for example - getting a 1 on one die roll does not affect the probability of getting a 1 on a second roll). Similarly - when we assert that two random variables are i






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






19. Probability of accepting a false null hypothesis.






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






21. 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.






22. Is a measure of the 'peakedness' of the probability distribution of a real-valued random variable. Higher kurtosis means more of the variance is due to infrequent extreme deviations - as opposed to frequent modestly sized deviations.






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






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






25. 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






26. S^2






27. A measurement such that the random error is small






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






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






30. 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.






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






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






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






34.






35. ?






36. (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






37. 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






38. Rejecting a true null hypothesis.






39. Patterns in the data may be modeled in a way that accounts for randomness and uncertainty in the observations - and are then used for drawing inferences about the process or population being studied; this is called






40. 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.






41. Is a sample space over which a probability measure has been defined.






42. Are two related but separate academic disciplines. Statistical analysis often uses probability distributions - and the two topics are often studied together. However - probability theory contains much that is of mostly of mathematical interest and no






43. Some commonly used symbols for sample statistics






44. 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.






45. 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.






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






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






48. 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.






49. Any specific experimental condition applied to the subjects






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