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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 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'






2. 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.






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






4. Is the probability of two events occurring together. The joint probability of A and B is written P(A and B) or P(A - B).






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






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






7. (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






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






9. 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






10. Is the most commonly used measure of statistical dispersion. It is the square root of the variance - and is generally written s (sigma).






11. 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.






12. (e.g. ? - b) are commonly used to denote unknown parameters (population parameters).






13. 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.






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






15. 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






16. 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.






17. (cdfs) are denoted by upper case letters - e.g. F(x).






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






19. Another name for elementary event.






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






21. ?






22. Rejecting a true null hypothesis.






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






24. Any specific experimental condition applied to the subjects






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






26. 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






27. 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






28. Probability of accepting a false null hypothesis.






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






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






31. 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.






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






33. (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






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






35. A subjective estimate of probability.






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






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






38. Failing to reject a false null hypothesis.






39. The probability distribution of a sample statistic based on all the possible simple random samples of the same size from a population.






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






41. 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






42. Is the function that gives the probability distribution of a random variable. It cannot be negative - and its integral on the probability space is equal to 1.






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






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






45. Have both a meaningful zero value and the distances between different measurements defined; they provide the greatest flexibility in statistical methods that can be used for analyzing the data






46. 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






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






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






49. 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






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