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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 the probability of an event - ignoring any information about other events. The marginal probability of A is written P(A). Contrast with conditional probability.






2. 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






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






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






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






6. 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






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






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






9. 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.






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






11. Probability of rejecting a true null hypothesis.






12. Failing to reject a false null hypothesis.






13. Is a sample space over which a probability measure has been defined.






14. 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






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






16. A subjective estimate of probability.






17. 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






18. Consists of a number of independent trials repeated under identical conditions. On each trial - there are two possible outcomes.






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






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






21. 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.






22. (e.g. ? - b) are commonly used to denote unknown parameters (population parameters).






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






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






25. (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.






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






27. Used to reduce bias - this measure weights the more relevant information higher than less relevant info.






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






29. 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






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






31. 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.






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






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






34. Probability of accepting a false null hypothesis.






35. Var[X] :






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. Samples are drawn from two different populations such that there is a matching of the first sample data drawn and a corresponding data value in the second sample data.






38. 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).






39. Another name for elementary event.






40. 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.






41. A list of individuals from which the sample is actually selected.






42. (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






43. Some commonly used symbols for population parameters






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






45. 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.






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






47. 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.






48. 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.






49. Is defined as the expected value of random variable (X -






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