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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. 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






2. 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.






3. Some commonly used symbols for sample statistics






4. (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.






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






6. Are two related but separate academic disciplines. Statistical analysis often uses probability distributions - and the two topics are often studied together. However - probability theory contains much that is of mostly of mathematical interest and no






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






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






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






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






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. To prove the guiding theory further - these predictions are tested as well - as part of the scientific method. If the inference holds true - then the descriptive statistics of the new data increase the soundness of that






13. 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).






14. E[X] :






15. 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






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






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






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






19. 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)






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






21. 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.






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






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






24. 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.






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






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






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






28. 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






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






30. Cov[X - Y] :






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






32. A list of individuals from which the sample is actually selected.






33. 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.






34. Failing to reject a false null hypothesis.






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






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






37. The probability of correctly detecting a false null hypothesis.






38. 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.






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






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






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






43. 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






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






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






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






47. 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'






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






49. Any specific experimental condition applied to the subjects






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







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