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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. 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






2. Changes over time that show a regular periodicity in the data where regular means over a fixed interval; the time between repetitions is called the period.






3. Is data that can take only two values - usually represented by 0 and 1.






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






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






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






7. 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.






8. Cov[X - Y] :






9. (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.






10. (or expectation) of a random variable is the sum of the probability of each possible outcome of the experiment multiplied by its payoff ('value'). Thus - it represents the average amount one 'expects' to win per bet if bets with identical odds are re






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






12. 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






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






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






15. Planning the research - including finding the number of replicates of the study - using the following information: preliminary estimates regarding the size of treatment effects - alternative hypotheses - and the estimated experimental variability. Co






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






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






18. 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.






19. 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.






20. ?r






21. 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).






22. A variable has a value or numerical measurement for which operations such as addition or averaging make sense.






23. Involves taking measurements of the system under study - manipulating the system - and then taking additional measurements using the same procedure to determine if the manipulation has modified the values of the measurements.






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






25. 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






26. 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






27. A sample selected in such a way that each individual is equally likely to be selected as well as any group of size n is equally likely to be selected.






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






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






30. 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






31. Performing the experiment following the experimental protocol and analyzing the data following the experimental protocol. 4. Further examining the data set in secondary analyses - to suggest new hypotheses for future study. 5. Documenting and present






32. A pairwise independent collection of random variables is a set of random variables any two of which are independent.






33. 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.






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






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






36. A subjective estimate of probability.






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






38. 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.






39. 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.






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






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






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

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






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






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






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






47. Probability of rejecting a true null hypothesis.






48. Data are gathered and correlations between predictors and response are investigated.






49. Failing to reject a false null hypothesis.






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






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