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






2. S^2






3. 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.






4. Var[X] :






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






6. 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.






7. Samples are drawn from two different populations such that there is a matching of the first sample data drawn and a corresponding data value in the second sample data.






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






9. 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






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






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






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






13. 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)






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






15. 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}.






16. 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.






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






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






19. 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.






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






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






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






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






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






25. 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.






26. 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






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






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






29. 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.






30. 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.






31. Have no meaningful rank order among values.






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






33. Is the study of the collection - organization - analysis - and interpretation of data. It deals with all aspects of this - including the planning of data collection in terms of the design of surveys and experiments.






34. 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.






35. Can be - for example - the possible outcomes of a dice roll (but it is not assigned a value). The distribution function of a random variable gives the probability of different results. We can also derive the mean and variance of a random variable.






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






37. Some commonly used symbols for sample statistics






38. A subjective estimate of probability.






39. Where the null hypothesis fails to be rejected and an actual difference between populations is missed giving a 'false negative'.






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






41. 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






42. Given two jointly distributed random variables X and Y - the marginal distribution of X is simply the probability distribution of X ignoring information about Y.






43. ?






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






45. 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






46. The standard deviation of a sampling distribution.






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






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






49. 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






50. Working from a null hypothesis two basic forms of error are recognized:







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