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. Another name for elementary event.






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






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






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






5. 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'






6. The collection of all possible outcomes in an experiment.






7. Can be - for example - the possible outcomes of a dice roll (but it is not assigned a value). The distribution function of a random variable gives the probability of different results. We can also derive the mean and variance of a random variable.






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






9. Failing to reject a false null hypothesis.






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






11. S^2






12. 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.






13. Is the function that gives the probability distribution of a random variable. It cannot be negative - and its integral on the probability space is equal to 1.






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






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






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






17. Is a sample space over which a probability measure has been defined.






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






19. 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.






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






21. Where the null hypothesis fails to be rejected and an actual difference between populations is missed giving a 'false negative'.






22. (cdfs) are denoted by upper case letters - e.g. F(x).






23. 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






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






25. 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






26. 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






27. 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






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






29. (or just likelihood) is a conditional probability function considered a function of its second argument with its first argument held fixed. For example - imagine pulling a numbered ball with the number k from a bag of n balls - numbered 1 to n. Then






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






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






33. A numerical facsimilie or representation of a real-world phenomenon.






34. (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.






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






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






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






38. Cov[X - Y] :






39. The probability distribution of a sample statistic based on all the possible simple random samples of the same size from a population.






40. Is a sample and the associated data points.






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






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






43. A measurement such that the random error is small






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






45. Is the probability of an event - ignoring any information about other events. The marginal probability of A is written P(A). Contrast with conditional probability.






46. 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.






47. 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).






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






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






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