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CLEP General Mathematics: Probability And Statistics

Subjects : clep, math
Instructions:
  • Answer 50 questions in 15 minutes.
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  • Match each statement with the correct term.
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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. S^2






2. Describes the spread in the values of the sample statistic when many samples are taken.






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






4. 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.






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






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






7. Is a measure of the asymmetry of the probability distribution of a real-valued random variable. Roughly speaking - a distribution has positive skew (right-skewed) if the higher tail is longer and negative skew (left-skewed) if the lower tail is longe






8. (or multivariate random variable) is a vector whose components are random variables on the same probability space.






9. ?






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. 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).






12. Some commonly used symbols for population parameters






13. 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






14. 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.






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






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






17. 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






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






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






20. 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






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






22. 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






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






24. 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'






25. To find the median value of a set of numbers: Arrange the numbers in numerical order. Locate the two middle numbers in the list. Find the average of those two middle values.






26. Is denoted by - pronounced 'x bar'.






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






28. 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.






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






30. Var[X] :






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






32. Some commonly used symbols for sample statistics






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






34. (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






35. When you have two or more competing models - choose the simpler of the two models.






36. 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






37. ?r






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






39. 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.






40. Is a measure of the 'peakedness' of the probability distribution of a real-valued random variable. Higher kurtosis means more of the variance is due to infrequent extreme deviations - as opposed to frequent modestly sized deviations.






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






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






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






44. 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)






45. 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.






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






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






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






49. 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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50. 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