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






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






3. 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






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






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






6. 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).






7. ?






8. 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.






9. 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.






10. 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.






11. Cov[X - Y] :






12. 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.






13. 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






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






15. 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.






16. Failing to reject a false null hypothesis.






17. 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






18. 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






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






20. Is denoted by - pronounced 'x bar'.






21. 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.






22. Is its expected value. The mean (or sample mean of a data set is just the average value.






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






24. 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






25. 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.






26. E[X] :






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






28. Any specific experimental condition applied to the subjects






29. (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.






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






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






32. There are four main levels of measurement used in statistics: Each of these have different degrees of usefulness in statistical research.






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






34. Long-term upward or downward movement over time.






35. The standard deviation of a sampling distribution.






36. 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






37. 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






38. When you have two or more competing models - choose the simpler of the two models.






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






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






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






42. Rejecting a true null hypothesis.






43. Is used to describe probability in a continuous probability distribution. For example - you can't say that the probability of a man being six feet tall is 20% - but you can say he has 20% of chances of being between five and six feet tall. Probabilit






44. Is that part of a population which is actually observed.






45. Ratio and interval measurements which can be either discrete or continuous - due to their numerical nature are grouped together as






46. 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






47. 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.






48. 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.






49. Var[X] :






50. Probability of accepting a false null hypothesis.