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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. Gives the probability of events in a probability space.






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






3. 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.






4. Any specific experimental condition applied to the subjects






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






6. Some commonly used symbols for population parameters






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






8. 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.






9. 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.






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






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






12. Probability of accepting a false null hypothesis.






13. Statistics involve methods of organizing - picturing - and summarizing information from samples or population.






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






15. Failing to reject a false null hypothesis.






16. Is a parameter that indexes a family of probability distributions.






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






18. The standard deviation of a sampling distribution.






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






20. 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






21. 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






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






23. 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






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






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






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. 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.






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






29. Is the result of applying a statistical algorithm to a data set. It can also be described as an observable random variable.






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






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






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






33. 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






34. To prove the guiding theory further - these predictions are tested as well - as part of the scientific method. If the inference holds true - then the descriptive statistics of the new data increase the soundness of that






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






36. 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}.






37.






38. 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.






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






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






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






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






43. In the long run - as the sample size increases - the relative frequencies of outcomes approach to the theoretical probability.






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






45. Ratio and interval measurements which can be either discrete or continuous - due to their numerical nature are grouped together as






46. 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






47. 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






48. S^2






49. Is the length of the smallest interval which contains all the data.






50. (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







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