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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 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.






2. Probability of rejecting a true null hypothesis.






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






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






5. Data are gathered and correlations between predictors and response are investigated.






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






7. 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






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






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






10. 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






11. 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






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






13. 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






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






15. 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






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






17. Given two jointly distributed random variables X and Y - the marginal distribution of X is simply the probability distribution of X ignoring information about Y.






18. 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.






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






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






21. 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)






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






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






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






25. 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






26. ?






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






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






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






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






31. 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






32. A collection of events is mutually independent if for any subset of the collection - the joint probability of all events occurring is equal to the product of the joint probabilities of the individual events. Think of the result of a series of coin-fl






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






34. (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






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






36. Have no meaningful rank order among values.






37. 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).






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






39. 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.






40. 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






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






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






43. Any specific experimental condition applied to the subjects






44. 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.






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






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






47. 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






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






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






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