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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. Any specific experimental condition applied to the subjects






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






3. In particular - the pdf of the standard normal distribution is denoted by






4. Rejecting a true null hypothesis.






5. 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






6. Probability of rejecting a true null hypothesis.






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






9. 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






10. Is a measure of its statistical dispersion - indicating how far from the expected value its values typically are. The variance of random variable X is typically designated as - - or simply s2.






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






12. Some commonly used symbols for population parameters






13. 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






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






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






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






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






18. Changes over time that show a regular periodicity in the data where regular means over a fixed interval; the time between repetitions is called the period.






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






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






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






22. 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






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






24. 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.






25. The objects described by a set of data: person (animal) - place - and - thing. (SUBJECTS)






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






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






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






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






30. S^2






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






32. 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






33. Probability of accepting a false null hypothesis.






34. 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






35. Another name for elementary event.






36. 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.






37. ?r






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






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






40. (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.






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






42. Some commonly used symbols for sample statistics






43. 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






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






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






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






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






48. 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.






49. 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).






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







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