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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. 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






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






3. 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.






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






5. Is a sample space over which a probability measure has been defined.






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






7. Long-term upward or downward movement over time.






8. 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'






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






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






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






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






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






14. 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.






15. 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).






16. 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.






17. Where the null hypothesis is falsely rejected giving a 'false positive'.






18. Is often denoted by placing a caret over the corresponding symbol - e.g. - pronounced 'theta hat'.






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






20. (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






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






22. 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






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






24. ?r






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






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






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






28.






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






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






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






33. 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






34. 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






35. Rejecting a true null hypothesis.






36. 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






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






38. 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.






39. 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.






40. 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






41. 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






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






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






44. E[X] :






45. 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






46. 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.






47. 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.






48. Another name for elementary event.






49. 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.






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