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






2. 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.






3. 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






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






5. 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.






6. 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.






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






8. A variable that has an important effect on the response variable and the relationship among the variables in a study but is not one of the explanatory variables studied either because it is unknown or not measured.






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






10. 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.






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






12. In the long run - as the sample size increases - the relative frequencies of outcomes approach to the theoretical probability.






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






14. Is a typed measurement - it can be a boolean value - a real number - a vector (in which case it's also called a data vector) - etc.






15. 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






16. A data value that falls outside the overall pattern of the graph.






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






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






19. Some commonly used symbols for sample statistics






20. Any specific experimental condition applied to the subjects






21. 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






22. (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






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






24. 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






25. Another name for elementary event.






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






27. 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






28. Where the null hypothesis fails to be rejected and an actual difference between populations is missed giving a 'false negative'.






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






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






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






32. E[X] :






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






34. Probability of accepting a false null hypothesis.






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






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






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






38. (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.






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






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






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






42. 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}.






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






44. Have no meaningful rank order among values.






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






46. Is a sample and the associated data points.






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






48. Var[X] :






49. S^2






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







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