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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. 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.






2. Performing the experiment following the experimental protocol and analyzing the data following the experimental protocol. 4. Further examining the data set in secondary analyses - to suggest new hypotheses for future study. 5. Documenting and present






3. 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.






4. To prove the guiding theory further - these predictions are tested as well - as part of the scientific method. If the inference holds true - then the descriptive statistics of the new data increase the soundness of that






5. Any specific experimental condition applied to the subjects






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






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






8. A subjective estimate of probability.






9. There are two major types of causal statistical studies: In both types of studies - the effect of differences of an independent variable (or variables) on the behavior of the dependent variable are observed. The difference between the two types lies






10. 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






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






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






13. 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).






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






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






16. 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






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






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






19. 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.






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






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






22. 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.






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






24. ?






25. 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






26. Is a sample and the associated data points.






27. Are usually written with upper case calligraphic (e.g. F for the set of sets on which we define the probability P)






28. 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






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






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






31. Some commonly used symbols for sample statistics






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






33. 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






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






35. Is the result of applying a statistical algorithm to a data set. It can also be described as an observable random variable.






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






37. Failing to reject a false null hypothesis.






38. 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.






39. Where the null hypothesis is falsely rejected giving a 'false positive'.






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






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






42. 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.






43. 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.






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. 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.






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






47. Is the probability distribution - under repeated sampling of the population - of a given statistic.






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






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






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