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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 defined as the expected value of random variable (X -






2. 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






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






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






5. Rejecting a true null hypothesis.






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






7. Probability of accepting a false null hypothesis.






8. 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






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






10. When info. in a contingency table is re-organized into more or less categories - relationships seen can change or reverse.

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






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






13. 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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14. Is a sample and the associated data points.






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






16. Given two jointly distributed random variables X and Y - the marginal distribution of X is simply the probability distribution of X ignoring information about Y.






17. 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






18.






19. A pairwise independent collection of random variables is a set of random variables any two of which are independent.






20. 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






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






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






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






24. Another name for elementary event.






25. ?






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






27. 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






28. Is used in 'mathematical statistics' (alternatively - 'statistical theory') to study the sampling distributions of sample statistics and - more generally - the properties of statistical procedures. The use of any statistical method is valid when the






29. 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.






30. 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.






31. Two variables such that their effects on the response variable cannot be distinguished from each other.






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






33. 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.






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






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






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






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






38. 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.






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






40. 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.






41. 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






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






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






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






46. Have no meaningful rank order among values.






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






48. 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.






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






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






Can you answer 50 questions in 15 minutes?



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