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






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






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






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






5. Probability of rejecting a true null hypothesis.






6. To find the average - or arithmetic mean - of a set of numbers:






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






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






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






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






11. 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)






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






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

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






15. Rejecting a true null hypothesis.






16. 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.






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






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






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






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






21. 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






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






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






24. 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.






25. ?r






26. In Bayesian inference - this represents prior beliefs or other information that is available before new data or observations are taken into account.






27.






28. 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






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






30. Is used in 'mathematical statistics' (alternatively - 'statistical theory') to study the sampling distributions of sample statistics and - more generally - the properties of statistical procedures. The use of any statistical method is valid when the






31. When there is an even number of values...






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






33. Interpretation of statistical information in that the assumption is that whatever is proposed as a cause has no effect on the variable being measured can often involve the development of a






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






35. 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.






36. Cov[X - Y] :






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






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






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






40. Uses patterns in the sample data to draw inferences about the population represented - accounting for randomness. These inferences may take the form of: answering yes/no questions about the data (hypothesis testing) - estimating numerical characteris






41. 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}.






42. Statistics involve methods of using information from a sample to draw conclusions regarding the population.






43. Var[X] :






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






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






46. Is the function that gives the probability distribution of a random variable. It cannot be negative - and its integral on the probability space is equal to 1.






47. 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.






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






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






50. A measure that is relevant or appropriate as a representation of that property.