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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. The collection of all possible outcomes in an experiment.






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






3. Is a sample and the associated data points.






4. 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.






5. 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






6. 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






7. ?






8. 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






9. Some commonly used symbols for population parameters






10. 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.






11. 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.






12. 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.






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






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






15. (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.






16. Summarize the population data by describing what was observed in the sample numerically or graphically. Numerical descriptors include mean and standard deviation for continuous data types (like heights or weights) - while frequency and percentage are






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






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






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






20. A consistent - repeated deviation of the sample statistic from the population parameter in the same direction when many samples are taken.






21. 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






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






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






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






25. 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.






26. 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.






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






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

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






30. 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).






31. 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






32. (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






33. 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.






34. 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.






35. 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






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






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






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






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






40. Some commonly used symbols for sample statistics






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






42. Is a subset of the sample space - to which a probability can be assigned. For example - on rolling a die - 'getting a five or a six' is an event (with a probability of one third if the die is fair).






43. 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






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






45. Any specific experimental condition applied to the subjects






46. 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






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






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






49. 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.






50. A measurement such that the random error is small