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






2. Is a process of selecting observations to obtain knowledge about a population. There are many methods to choose on which sample to do the observations.






3. Can be a population parameter - a distribution parameter - an unobserved parameter (with different shades of meaning). In statistics - this is often a quantity to be estimated.

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






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






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






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






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






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






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






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






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






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






15. 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.






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






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

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






19. 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






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






21. Some commonly used symbols for sample statistics






22. S^2






23. 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






24. Another name for elementary event.






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






26. 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.






27. Are simply two different terms for the same thing. Add the given values






28. 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






29. 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






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






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






32. 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






33. Describes a characteristic of an individual to be measured or observed.






34. Given two jointly distributed random variables X and Y - the conditional probability distribution of Y given X (written 'Y | X') is the probability distribution of Y when X is known to be a particular value.






35. 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






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






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






38. (pdfs) and probability mass functions are denoted by lower case letters - e.g. f(x).






39. 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.






40. Is a typed measurement - it can be a boolean value - a real number - a vector (in which case it's also called a data vector) - etc.






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






42. 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






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






44. 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.






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






46. 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.






47. 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.






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






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






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