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CLEP General Mathematics: Probability And Statistics

Subjects : clep, math
Instructions:
  • Answer 50 questions in 15 minutes.
  • If you are not ready to take this test, you can study here.
  • 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 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.






2. 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






3. Any specific experimental condition applied to the subjects






4. 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






5. 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






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






7. 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






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






10. (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.






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






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. Var[X] :






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






15. 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.






16. 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'






17. 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.






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






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






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






21. 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






22. 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.






23. 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






24. A collection of events is mutually independent if for any subset of the collection - the joint probability of all events occurring is equal to the product of the joint probabilities of the individual events. Think of the result of a series of coin-fl






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






26. Another name for elementary event.






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






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






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






30. 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






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






32. 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.






33. S^2






34. ?






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






36. The standard deviation of a sampling distribution.






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






38. 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






39. Is a measure of its statistical dispersion - indicating how far from the expected value its values typically are. The variance of random variable X is typically designated as - - or simply s2.






40. Some commonly used symbols for sample statistics






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






42. Probability of rejecting a true null hypothesis.






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






44.






45. 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






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






47. Ratio and interval measurements which can be either discrete or continuous - due to their numerical nature are grouped together as






48. E[X] :






49. Probability of accepting a false null hypothesis.






50. 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.