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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. Descriptive statistics and inferential statistics (a.k.a. - predictive statistics) together comprise






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






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






4. 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






5. S^2






6. Is the length of the smallest interval which contains all the data.






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






8. 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.






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






10. There are two major types of causal statistical studies: In both types of studies - the effect of differences of an independent variable (or variables) on the behavior of the dependent variable are observed. The difference between the two types lies






11. 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






12. 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






13. 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.






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 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.






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






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






18. 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.






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






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






22. 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






23. Probability of accepting a false null hypothesis.






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






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






26. 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






27. 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.






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






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






30. Some commonly used symbols for sample statistics






31. (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






32. ?






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






34. 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






35. 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.






36. 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






37. A measurement such that the random error is small






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






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






40. Is the study of the collection - organization - analysis - and interpretation of data. It deals with all aspects of this - including the planning of data collection in terms of the design of surveys and experiments.






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






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






43. 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






44. 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






45. 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.






46. Probability of rejecting a true null hypothesis.






47. Is the probability of some event A - assuming event B. Conditional probability is written P(A|B) - and is read 'the probability of A - given B'






48. Var[X] :






49. Are usually written in upper case roman letters: X - Y - etc.






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