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






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






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






4. Probability of accepting a false null hypothesis.






5. Have meaningful distances between measurements defined - but the zero value is arbitrary (as in the case with longitude and temperature measurements in Celsius or Fahrenheit)






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






7. The errors - or difference between the estimated response y^i and the actual measured response yi - collectively






8. (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.






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






10. Is the set of possible outcomes of an experiment. For example - the sample space for rolling a six-sided die will be {1 - 2 - 3 - 4 - 5 - 6}.






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






12. Statistical methods can be used for summarizing or describing a collection of data; this is called






13. Cov[X - Y] :






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






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






16. 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.






17. Failing to reject a false null hypothesis.






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






19. Is the length of the smallest interval which contains all the data.






20. 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'






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






22. 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.






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






24. 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.






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






26. 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.






27.






28. 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.






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






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






31. 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






32. 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.






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






34. Have both a meaningful zero value and the distances between different measurements defined; they provide the greatest flexibility in statistical methods that can be used for analyzing the data






35. 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






36. 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






37. Probability of rejecting a true null hypothesis.






38. 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






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






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






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






42. Another name for elementary event.






43. 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.






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






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






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






47. Some commonly used symbols for sample statistics






48. 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.






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






50. 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.