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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. ?r






2. 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.






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






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






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






6. 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).






7. Patterns in the data may be modeled in a way that accounts for randomness and uncertainty in the observations - and are then used for drawing inferences about the process or population being studied; this is called






8. A measurement such that the random error is small






9. 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






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






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






12. Another name for elementary event.






13. When you have two or more competing models - choose the simpler of the two models.






14. 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'






15. 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.






16. 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.






17. 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






18. Some commonly used symbols for sample statistics






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






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






21. 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.






22. 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






23. Involves taking measurements of the system under study - manipulating the system - and then taking additional measurements using the same procedure to determine if the manipulation has modified the values of the measurements.






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






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






26. 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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27. 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






28. 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.






29. 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.






30. 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}.






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






32. When there is an even number of values...






33. The result of a Bayesian analysis that encapsulates the combination of prior beliefs or information with observed data






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






35. 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.






36. Rejecting a true null hypothesis.






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






38. Is a process of selecting observations to obtain knowledge about a population. There are many methods to choose on which sample to do the observations.






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






40. Design of experiments - using blocking to reduce the influence of confounding variables - and randomized assignment of treatments to subjects to allow unbiased estimates of treatment effects and experimental error. At this stage - the experimenters a






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






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






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






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






45. The standard deviation of a sampling distribution.






46. 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






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






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

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






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