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






2. Is a sample and the associated data points.






3. A subjective estimate of probability.






4. (or just likelihood) is a conditional probability function considered a function of its second argument with its first argument held fixed. For example - imagine pulling a numbered ball with the number k from a bag of n balls - numbered 1 to n. Then






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






6. A measurement such that the random error is small






7. 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.






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






9. Is a function of the known data that is used to estimate an unknown parameter; an estimate is the result from the actual application of the function to a particular set of data. The mean can be used as an estimator.






10. Is a parameter that indexes a family of probability distributions.






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






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






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






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






15. 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.






16. 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}.






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






18. Another name for elementary event.






19. 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






20. 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






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






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






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






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






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






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






28. ?






29. Have no meaningful rank order among values.






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






32. 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.






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






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






35. 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.






36. 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.






37. 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






38. 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






39. 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.






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






41. Can refer either to a sample not being representative of the population - or to the difference between the expected value of an estimator and the true value.






42. Are usually written with upper case calligraphic (e.g. F for the set of sets on which we define the probability P)






43. 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.






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






45. Statistical methods can be used for summarizing or describing a collection of data; this is called






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






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






48. 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






49. (or atomic event) is an event with only one element. For example - when pulling a card out of a deck - 'getting the jack of spades' is an elementary event - while 'getting a king or an ace' is not.






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







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