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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. To find the median value of a set of numbers: Arrange the numbers in numerical order. Locate the two middle numbers in the list. Find the average of those two middle values.






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






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






4. Some commonly used symbols for population parameters






5. 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.






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






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






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






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






10. ?






11. 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.


12. Have no meaningful rank order among values.






13. 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'






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






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






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






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






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






19. 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






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






21. 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






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






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






24. 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.






25. (or expectation) of a random variable is the sum of the probability of each possible outcome of the experiment multiplied by its payoff ('value'). Thus - it represents the average amount one 'expects' to win per bet if bets with identical odds are re






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






27. 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.






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






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






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






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






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


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






34. 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.






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






36. A group of individuals sharing some common features that might affect the treatment.






37. 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.






38. The standard deviation of a sampling distribution.






39.






40. 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






41. Given two random variables X and Y - the joint distribution of X and Y is the probability distribution of X and Y together.






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






43. 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.






44. 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)






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






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






47. Is data that can take only two values - usually represented by 0 and 1.






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






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






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