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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. Gives the probability distribution for a continuous random variable.






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






3. Cov[X - Y] :






4. 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.






5. (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






6. 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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7. 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.






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

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9. 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






10. The result of a Bayesian analysis that encapsulates the combination of prior beliefs or information with observed data






11. 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}.






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






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






14. 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.






15. Some commonly used symbols for population parameters






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






17. 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.






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






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






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






21. 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






22. 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






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






25. 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.






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






27. 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.






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






29.






30. 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.






31. 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.






32. Var[X] :






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






34. 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.






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






36. 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






37. 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






38. 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






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






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






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






43. Rejecting a true null hypothesis.






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






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






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






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






48. 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






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






50. 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.