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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 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






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






3. Rejecting a true null hypothesis.






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






5. A variable has a value or numerical measurement for which operations such as addition or averaging make sense.






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






7. 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.






8. A variable describes an individual by placing the individual into a category or a group.






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






10. (also called statistical variability) is a measure of how diverse some data is. It can be expressed by the variance or the standard deviation.






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






12. 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






13. The standard deviation of a sampling distribution.






14. 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.






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






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






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






18. 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).






19. 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.






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






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






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






23. A scale that represents an ordinal scale such as looks on a scale from 1 to 10.






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






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






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






27. 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.






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






29. (or multivariate random variable) is a vector whose components are random variables on the same probability space.






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






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






32. 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






33. 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






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






35. 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






36. Have meaningful distances between measurements defined - but the zero value is arbitrary (as in the case with longitude and temperature measurements in Celsius or Fahrenheit)






37. A subjective estimate of probability.






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






39. When info. in a contingency table is re-organized into more or less categories - relationships seen can change or reverse.


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






41. Any specific experimental condition applied to the subjects






42. A measurement such that the random error is small






43. Can be - for example - the possible outcomes of a dice roll (but it is not assigned a value). The distribution function of a random variable gives the probability of different results. We can also derive the mean and variance of a random variable.






44. 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.






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






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






47. Have both a meaningful zero value and the distances between different measurements defined; they provide the greatest flexibility in statistical methods that can be used for analyzing the data






48. Another name for elementary event.






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






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