Test your basic knowledge |

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. 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






2. A numerical measure that assesses the strength of a linear relationship between two variables.






3. 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.






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






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






6. Working from a null hypothesis two basic forms of error are recognized:






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






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






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






10. Also called correlation coefficient - is a numeric measure of the strength of linear relationship between two random variables (one can use it to quantify - for example - how shoe size and height are correlated in the population). An example is the P






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






12. Is a process of selecting observations to obtain knowledge about a population. There are many methods to choose on which sample to do the observations.






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






14. Can refer either to a sample not being representative of the population - or to the difference between the expected value of an estimator and the true value.






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






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






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






18. Rejecting a true null hypothesis.






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






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






21. 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).






22. The standard deviation of a sampling distribution.






23. E[X] :






24. Is defined as the expected value of random variable (X -






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






26. Have no meaningful rank order among values.






27. Var[X] :






28. 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






29. Another name for elementary event.






30. Is a sample and the associated data points.






31. S^2






32.






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






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






35. Probability of accepting a false null hypothesis.






36. 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






37. (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






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






39. A measure that is relevant or appropriate as a representation of that property.






40. 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






41. Occurs when a subject receives no treatment - but (incorrectly) believes he or she is in fact receiving treatment and responds favorably.






42. 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.






43. 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.






44. Some commonly used symbols for population parameters






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






46. 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.






47. 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






48. ?






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






50. Probability of rejecting a true null hypothesis.