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






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






3. Is defined as the expected value of random variable (X -






4. Samples are drawn from two different populations such that the sample data drawn from one population is completely unrelated to the selection of sample data from the other population.






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






6. 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.






7. Probability of rejecting a true null hypothesis.






8. 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.






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






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






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






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






13. 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.






14. Is used to describe probability in a continuous probability distribution. For example - you can't say that the probability of a man being six feet tall is 20% - but you can say he has 20% of chances of being between five and six feet tall. Probabilit






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






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






17. 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






18. 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.






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






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






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






22. 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.






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






24. 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'






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. Planning the research - including finding the number of replicates of the study - using the following information: preliminary estimates regarding the size of treatment effects - alternative hypotheses - and the estimated experimental variability. Co






27. ?r






28. A data value that falls outside the overall pattern of the graph.






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






30. A subjective estimate of probability.






31. 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.






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






33. Some commonly used symbols for sample statistics






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






35. 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.






36. 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






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






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






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






40. 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






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






42. 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






43. A numerical measure that describes an aspect of a population.






44. 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






45. 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.






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






47. Given two random variables X and Y - the joint distribution of X and Y is the probability distribution of X and Y together.






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






49. 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






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