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CLEP General Mathematics: Probability And Statistics

Subjects : clep, math
Instructions:
  • Answer 50 questions in 15 minutes.
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  • 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 scale that represents an ordinal scale such as looks on a scale from 1 to 10.






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






3. 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.






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






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






6. 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.






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






8. 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.






9. (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






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






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






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






13. Probability of rejecting a true null hypothesis.






14. A subjective estimate of probability.






15. E[X] :






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






17. Because variables conforming only to nominal or ordinal measurements cannot be reasonably measured numerically - sometimes they are grouped together as






18. Is the study of the collection - organization - analysis - and interpretation of data. It deals with all aspects of this - including the planning of data collection in terms of the design of surveys and experiments.






19. Is one that explores the correlation between smoking and lung cancer. This type of study typically uses a survey to collect observations about the area of interest and then performs statistical analysis. In this case - the researchers would collect o






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






21. 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}.






22. 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.






23. 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.






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






25. 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.






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






27. Have imprecise differences between consecutive values - but have a meaningful order to those values






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






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

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






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






32. Cov[X - Y] :






33. 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.






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






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






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






37. Some commonly used symbols for sample statistics






38. Probability of accepting a false null hypothesis.






39. 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






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






41. 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.






42. 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






43. There are two major types of causal statistical studies: In both types of studies - the effect of differences of an independent variable (or variables) on the behavior of the dependent variable are observed. The difference between the two types lies






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






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






46. 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.






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






48. Is used to describe probability in a continuous probability distribution. For example - you can't say that the probability of a man being six feet tall is 20% - but you can say he has 20% of chances of being between five and six feet tall. Probabilit






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






50. 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.