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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. 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






2. 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.






3. 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






4. 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






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






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






7. A subjective estimate of probability.






8. 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.






9. 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.






10. 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.






11. A measurement such that the random error is small






12. 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.






13. 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.






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






15. Probability of accepting a false null hypothesis.






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






17. 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






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






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






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






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






22. Have no meaningful rank order among values.






23. 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).






24. Some commonly used symbols for population parameters






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






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






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






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






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






30. A scale that represents an ordinal scale such as looks on a scale from 1 to 10.






31. A pairwise independent collection of random variables is a set of random variables any two of which are independent.






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






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






34. 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






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






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






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






38. 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.






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






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






41. 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.






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






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






44. 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.






45. Is a measure of the asymmetry of the probability distribution of a real-valued random variable. Roughly speaking - a distribution has positive skew (right-skewed) if the higher tail is longer and negative skew (left-skewed) if the lower tail is longe






46. Also called correlation coefficient - is a numeric measure of the strength of linear relationship between two random variables (one can use it to quantify - for example - how shoe size and height are correlated in the population). An example is the P






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






48. S^2






49. Used to reduce bias - this measure weights the more relevant information higher than less relevant info.






50. ?