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






2. A pairwise independent collection of random variables is a set of random variables any two of which are independent.






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






4. Rejecting a true null hypothesis.






5. 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.






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






7. 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






8. 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.






9. To find the average - or arithmetic mean - of a set of numbers:






10. 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






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






12. 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






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






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






15. A variable has a value or numerical measurement for which operations such as addition or averaging make sense.






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






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






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

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






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






21. 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.






22. A common goal for a statistical research project is to investigate causality - and in particular to draw a conclusion on the effect of changes in the values of predictors or independent variables on dependent variables or response.






23. 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






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






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






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






27. 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.






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






29. 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}.






30. 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.






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






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






33. 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'






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






35.






36. (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.






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






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






39. Failing to reject a false null hypothesis.






40. 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.






41. Used to reduce bias - this measure weights the more relevant information higher than less relevant info.






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






43. 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






44. 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.






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






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






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






48. S^2






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






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