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






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






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






4. Rejecting a true null hypothesis.






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






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






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






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






9. 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






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






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






12. 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.






13. Cov[X - Y] :






14. 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.






15. 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






16. E[X] :






17.






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






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






20. 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.






21. A subjective estimate of probability.






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






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






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






25. 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).






26. The standard deviation of a sampling distribution.






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






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






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






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






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. A variable that has an important effect on the response variable and the relationship among the variables in a study but is not one of the explanatory variables studied either because it is unknown or not measured.






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






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






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






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






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






38. 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






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






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






41. 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.






42. 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).






43. Is a set of entities about which statistical inferences are to be drawn - often based on random sampling. One can also talk about a population of measurements or values.






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






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






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






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






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






50. ?