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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. (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.






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






3. Rejecting a true null hypothesis.






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






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






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






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. 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.






9. 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.






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






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






12. Cov[X - Y] :






13. 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.






14. The standard deviation of a sampling distribution.






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






16. E[X] :






17. Probability of rejecting a true null hypothesis.






18. 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






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






20. 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.






21. Any specific experimental condition applied to the subjects






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






23. 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






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






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






26. 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






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






28. A list of individuals from which the sample is actually selected.






29. 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






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






31. (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






32. 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.






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






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






35. ?






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






37. 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






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






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






40. 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






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






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






43. 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}.






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






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






46. Are usually written in upper case roman letters: X - Y - etc.






47. 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






48. 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.






49. Design of experiments - using blocking to reduce the influence of confounding variables - and randomized assignment of treatments to subjects to allow unbiased estimates of treatment effects and experimental error. At this stage - the experimenters a






50. 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