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






2. 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.






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






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






5. Failing to reject a false null hypothesis.






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






7. 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.






8. 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






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






10. S^2






11. 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.






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






13. Uses patterns in the sample data to draw inferences about the population represented - accounting for randomness. These inferences may take the form of: answering yes/no questions about the data (hypothesis testing) - estimating numerical characteris






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






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






16. The standard deviation of a sampling distribution.






17. 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






18. A variable that has an important effect on the response variable and the relationship among the variables in a study but is not one of the explanatory variables studied either because it is unknown or not measured.






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






20. ?






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






22. 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






23. 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)






24. 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.






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






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






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






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






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






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






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






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






33. Rejecting a true null hypothesis.






34. 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.






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






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






37. (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.






38. 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.






39. The objects described by a set of data: person (animal) - place - and - thing. (SUBJECTS)






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






41. A numerical measure that describes an aspect of a sample.






42. 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






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






44. Error also refers to the extent to which individual observations in a sample differ from a central value - such as






45. When there is an even number of values...






46. Any specific experimental condition applied to the subjects






47. Is one that explores the correlation between smoking and lung cancer. This type of study typically uses a survey to collect observations about the area of interest and then performs statistical analysis. In this case - the researchers would collect o






48. 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






49. 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






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