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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. 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






2. 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






3.






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






5. Var[X] :






6. 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






7. Have no meaningful rank order among values.






8. 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).






9. 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.






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






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






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






13. 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.






14. 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.






15. 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






16. Is that part of a population which is actually observed.






17. 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.






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






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






20. Given two random variables X and Y - the joint distribution of X and Y is the probability distribution of X and Y together.






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






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






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






24. 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)






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






26. 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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27. 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.






28. 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}.






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






30. (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






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






32. A variable describes an individual by placing the individual into a category or a group.






33. Where the null hypothesis is falsely rejected giving a 'false positive'.






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






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






37. 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.






38. Some commonly used symbols for population parameters






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






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






41. A variable has a value or numerical measurement for which operations such as addition or averaging make sense.






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






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






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






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






46. Performing the experiment following the experimental protocol and analyzing the data following the experimental protocol. 4. Further examining the data set in secondary analyses - to suggest new hypotheses for future study. 5. Documenting and present






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






48. 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






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






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