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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. (or expectation) of a random variable is the sum of the probability of each possible outcome of the experiment multiplied by its payoff ('value'). Thus - it represents the average amount one 'expects' to win per bet if bets with identical odds are re






2. ?r






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






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






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






6. Probability of accepting a false null hypothesis.






7. Is the set of possible outcomes of an experiment. For example - the sample space for rolling a six-sided die will be {1 - 2 - 3 - 4 - 5 - 6}.






8. 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.






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






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






11. 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.






12. 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






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






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






15. 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.






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






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






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






19. 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






20. 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)






21. Statistics involve methods of organizing - picturing - and summarizing information from samples or population.






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






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






24. To find the median value of a set of numbers: Arrange the numbers in numerical order. Locate the two middle numbers in the list. Find the average of those two middle values.






25. Var[X] :






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






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






28. 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.






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






30. 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.






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






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






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






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






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






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






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






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






40. The proportion of the explained variation by a linear regression model in the total variation.






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

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42. ?






43. Many statistical methods seek to minimize the mean-squared error - and these are called






44. Statistics involve methods of using information from a sample to draw conclusions regarding the population.






45. 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






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






47. A pairwise independent collection of random variables is a set of random variables any two of which are independent.






48. 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.






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






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