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






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






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






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






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






6. Some commonly used symbols for population parameters






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






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






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






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






12. Is a set of entities about which statistical inferences are to be drawn - often based on random sampling. One can also talk about a population of measurements or values.






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






15. A numerical measure that assesses the strength of a linear relationship between two variables.






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






17. Cov[X - Y] :






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






19. A subjective estimate of probability.






20. Is a process of selecting observations to obtain knowledge about a population. There are many methods to choose on which sample to do the observations.






21. Is the exact middle value of a set of numbers Arrange the numbers in numerical order. Find the value in the middle of the list.






22. Descriptive statistics and inferential statistics (a.k.a. - predictive statistics) together comprise






23. The result of a Bayesian analysis that encapsulates the combination of prior beliefs or information with observed data






24. Probability of rejecting a true null hypothesis.






25. 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






26. 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)






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






28. (cdfs) are denoted by upper case letters - e.g. F(x).






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






30. 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






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






32. 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.






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






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






35. Another name for elementary event.






36. 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






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






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






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. 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






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






42. A measurement such that the random error is small






43. Failing to reject a false null hypothesis.






44. Are usually written in upper case roman letters: X - Y - etc.






45. Is often denoted by placing a caret over the corresponding symbol - e.g. - pronounced 'theta hat'.






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






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






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






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






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