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






2. 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.






3. 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.






4. (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






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






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






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






8. 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.






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






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






11. Failing to reject a false null hypothesis.






12. E[X] :






13. Rejecting a true null hypothesis.






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

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






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






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






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






19. The standard deviation of a sampling distribution.






20. Can be a population parameter - a distribution parameter - an unobserved parameter (with different shades of meaning). In statistics - this is often a quantity to be estimated.

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






22. 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






23. 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






24. ?






25. Given two jointly distributed random variables X and Y - the conditional probability distribution of Y given X (written 'Y | X') is the probability distribution of Y when X is known to be a particular value.






26. 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






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






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






29. In particular - the pdf of the standard normal distribution is denoted by






30. 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.






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






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






33. 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






34. Of a group of numbers is the center point of all those number values.






35. A group of individuals sharing some common features that might affect the treatment.






36. Is a set of entities about which statistical inferences are to be drawn - often based on random sampling. One can also talk about a population of measurements or values.






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






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






39. (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






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






41. 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)






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






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






44. Is a sample and the associated data points.






45. 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.






46. 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






47. 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.






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






49. 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).






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







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