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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 its expected value. The mean (or sample mean of a data set is just the average value.






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






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






4. 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






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






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






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






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






9. 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.






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






11. Cov[X - Y] :






12. Any specific experimental condition applied to the subjects






13. 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






14. E[X] :






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






16. Probability of accepting a false null hypothesis.






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






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






19. (or just likelihood) is a conditional probability function considered a function of its second argument with its first argument held fixed. For example - imagine pulling a numbered ball with the number k from a bag of n balls - numbered 1 to n. Then






20. 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.






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






22. 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






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






24. 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






25. 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






26. 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.






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






28. 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






29. Another name for elementary event.






30. 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






31. 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






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






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






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






35. Statistical methods can be used for summarizing or describing a collection of data; this is called






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






37. (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






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






39. Have both a meaningful zero value and the distances between different measurements defined; they provide the greatest flexibility in statistical methods that can be used for analyzing the data






40. ?






41. 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






42. S^2






43. Is a sample and the associated data points.






44. 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).






45. Rejecting a true null hypothesis.






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






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






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






49. 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.






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