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






2. 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.






3. 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.






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






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






6. 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.






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






8. 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.






9. A subjective estimate of probability.






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






11. Failing to reject a false null hypothesis.






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 measure that is relevant or appropriate as a representation of that property.






14. A measurement such that the random error is small






15. 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






16. Probability of accepting a false null hypothesis.






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






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






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






20. 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






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






22. In the long run - as the sample size increases - the relative frequencies of outcomes approach to the theoretical probability.






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






24. 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.






25. Another name for elementary event.






26. 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.






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






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






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






30. 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.






31. Any specific experimental condition applied to the subjects






32. Some commonly used symbols for sample statistics






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






34. 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.






35. Probability of rejecting a true null hypothesis.






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






37. Rejecting a true null hypothesis.






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






39. 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






40. 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).






41. 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.






42. Cov[X - Y] :






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






44. Have no meaningful rank order among values.






45. 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






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






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






48. Of a group of numbers is the center point of all those number values.






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






50. 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)