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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. 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






2. A consistent - repeated deviation of the sample statistic from the population parameter in the same direction when many samples are taken.






3. Cov[X - Y] :






4. (or atomic event) is an event with only one element. For example - when pulling a card out of a deck - 'getting the jack of spades' is an elementary event - while 'getting a king or an ace' is not.






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






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






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






8. 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.






9. The standard deviation of a sampling distribution.






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






11. Is a sample and the associated data points.






12. 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






13. Some commonly used symbols for sample statistics






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






15. (pdfs) and probability mass functions are denoted by lower case letters - e.g. f(x).






16. 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.






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






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






19. 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.






20. Rejecting a true null hypothesis.






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






22. 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).






23. S^2






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






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






26. ?






27. 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.






28. Is data arising from counting that can take only non-negative integer values.






29. 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






30. 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






31. When info. in a contingency table is re-organized into more or less categories - relationships seen can change or reverse.

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






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






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






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






36. Probability of accepting a false null hypothesis.






37. Var[X] :






38. A common goal for a statistical research project is to investigate causality - and in particular to draw a conclusion on the effect of changes in the values of predictors or independent variables on dependent variables or response.






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






40. 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






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






42. Is a subset of the sample space - to which a probability can be assigned. For example - on rolling a die - 'getting a five or a six' is an event (with a probability of one third if the die is fair).






43. 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






44. 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






45. Any specific experimental condition applied to the subjects






46. 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.






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






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






49. 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.






50. 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.