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






2. 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.






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






4. Cov[X - Y] :






5. Are usually written in upper case roman letters: X - Y - etc.






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






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






8. 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.






9. 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.






10. 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






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






12. There are four main levels of measurement used in statistics: Each of these have different degrees of usefulness in statistical research.






13. 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






14. E[X] :






15. 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.






16. 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.






17. 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.






18. 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






19. 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.






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






21. 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.






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






23. 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






24. 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.






25. Is the probability of two events occurring together. The joint probability of A and B is written P(A and B) or P(A - B).






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






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






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






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






30. 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.






31. 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






32. (or multivariate random variable) is a vector whose components are random variables on the same probability space.






33. Any specific experimental condition applied to the subjects






34. In number theory - scatter plots of data generated by a distribution function may be transformed with familiar tools used in statistics to reveal underlying patterns - which may then lead to






35. ?r






36. 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






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






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






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






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






41. Probability of accepting a false null hypothesis.






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






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

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






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






46. Var[X] :






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






49. Planning the research - including finding the number of replicates of the study - using the following information: preliminary estimates regarding the size of treatment effects - alternative hypotheses - and the estimated experimental variability. Co






50. 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