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






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






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






4. 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






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






6. 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






7. Where the null hypothesis is falsely rejected giving a 'false positive'.






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






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






10. 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.






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






12. 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.






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






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






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






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






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






18. A variable has a value or numerical measurement for which operations such as addition or averaging make sense.






19. 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.






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






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






22. Var[X] :






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






24. To prove the guiding theory further - these predictions are tested as well - as part of the scientific method. If the inference holds true - then the descriptive statistics of the new data increase the soundness of that






25. 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.






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






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






28. (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.






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






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


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






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






33. Another name for elementary event.






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






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






36. 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.






37. 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.






38. 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






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






40. 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.






41. Is a function of the known data that is used to estimate an unknown parameter; an estimate is the result from the actual application of the function to a particular set of data. The mean can be used as an estimator.






42. Probability of accepting a false null hypothesis.






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






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






45. 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.






46. 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.






47. A measurement such that the random error is small






48. Is its expected value. The mean (or sample mean of a data set is just the average value.






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






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