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






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






3. 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






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






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






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






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






8. Some commonly used symbols for sample statistics






9. 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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10. 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}.






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






12. (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.






13. Gives the probability distribution for a continuous random variable.






14. Consists of a number of independent trials repeated under identical conditions. On each trial - there are two possible outcomes.






15. Probability of rejecting a true null hypothesis.






16. Error also refers to the extent to which individual observations in a sample differ from a central value - such as






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






18. Are usually written with upper case calligraphic (e.g. F for the set of sets on which we define the probability P)






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






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






21. In number theory - scatter plots of data generated by a distribution function may be transformed with familiar tools used in statistics to reveal underlying patterns - which may then lead to






22. 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






23. 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






24. 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






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






26. Probability of accepting a false null hypothesis.






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






28. (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






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






30. 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.






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






32. 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






33. 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.






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






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






36. 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)






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

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38. Cov[X - Y] :






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






40. 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).






41. 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






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






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






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






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






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






47. Have no meaningful rank order among values.






48. Is its expected value. The mean (or sample mean of a data set is just the average value.






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






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