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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. Is denoted by - pronounced 'x bar'.






2. 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.






3. 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'






4. Two events are independent if the outcome of one does not affect that of the other (for example - getting a 1 on one die roll does not affect the probability of getting a 1 on a second roll). Similarly - when we assert that two random variables are i






5. Cov[X - Y] :






6. Data are gathered and correlations between predictors and response are investigated.






7. 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






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






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






10. (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.






11. (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






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






13. Is inference about a population from a random sample drawn from it or - more generally - about a random process from its observed behavior during a finite period of time.






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






15. S^2






16.






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






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






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






20. 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






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






22. 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.






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






24. 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






25. Failing to reject a false null hypothesis.






26. A sample selected in such a way that each individual is equally likely to be selected as well as any group of size n is equally likely to be selected.






27. ?






28. Some commonly used symbols for population parameters






29. Is a sample and the associated data points.






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






31. 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






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






33. Any specific experimental condition applied to the subjects






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






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






36. Many statistical methods seek to minimize the mean-squared error - and these are called






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






38. (pdfs) and probability mass functions are denoted by lower case letters - e.g. f(x).






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






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






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






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






43. 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.






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






45. 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.






46. 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






47. Is the result of applying a statistical algorithm to a data set. It can also be described as an observable random variable.






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






50. 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.