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






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






3. A subjective estimate of probability.






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






5. 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






6. Also called correlation coefficient - is a numeric measure of the strength of linear relationship between two random variables (one can use it to quantify - for example - how shoe size and height are correlated in the population). An example is the P






7. ?r






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






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






10. 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.






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






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






13. (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






14. 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.






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






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






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






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






19. 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.


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






21. Is the set of possible outcomes of an experiment. For example - the sample space for rolling a six-sided die will be {1 - 2 - 3 - 4 - 5 - 6}.






22. 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.






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






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






25. Is a sample and the associated data points.






26. Another name for elementary event.






27. Is the probability of some event A - assuming event B. Conditional probability is written P(A|B) - and is read 'the probability of A - given B'






28. Var[X] :






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






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






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






32. 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






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






34. E[X] :






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






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






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






38. 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






39. (also called statistical variability) is a measure of how diverse some data is. It can be expressed by the variance or the standard deviation.






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






41. 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






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






43. Can refer either to a sample not being representative of the population - or to the difference between the expected value of an estimator and the true value.






44. 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






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






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






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






48. 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).






49. 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






50. 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