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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. 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}.






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






3. 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.






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






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






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






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






8. Is a sample and the associated data points.






9. 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






10. Any specific experimental condition applied to the subjects






11. Is a measure of its statistical dispersion - indicating how far from the expected value its values typically are. The variance of random variable X is typically designated as - - or simply s2.






12. Are simply two different terms for the same thing. Add the given values






13. Rejecting a true null hypothesis.






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






15. A data value that falls outside the overall pattern of the graph.






16. (pdfs) and probability mass functions are denoted by lower case letters - e.g. f(x).






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






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






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. 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






21. Have meaningful distances between measurements defined - but the zero value is arbitrary (as in the case with longitude and temperature measurements in Celsius or Fahrenheit)






22. 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.






23. 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






24. Ratio and interval measurements which can be either discrete or continuous - due to their numerical nature are grouped together as






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






26. 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.






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






28. Is the length of the smallest interval which contains all the data.






29. A measurement such that the random error is small






30. Is used in 'mathematical statistics' (alternatively - 'statistical theory') to study the sampling distributions of sample statistics and - more generally - the properties of statistical procedures. The use of any statistical method is valid when the






31. 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






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






33. 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.






34. 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.






35. 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






36. ?






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






38. 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






39. 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






40. 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






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






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






43. Failing to reject a false null hypothesis.






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






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






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






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






48. Of a group of numbers is the center point of all those number values.






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






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