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






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


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






4. 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.






5. 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.






6. Is the result of applying a statistical algorithm to a data set. It can also be described as an observable random variable.






7. 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.






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






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. 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.






11. Another name for elementary event.






12. 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.






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






14. 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.






15. 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






16. 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.






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






18. 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






19. ?






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






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






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






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






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






25. 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






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






27. Descriptive statistics and inferential statistics (a.k.a. - predictive statistics) together comprise






28. 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.






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






30. Probability of accepting a false null hypothesis.






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






32. Is a sample and the associated data points.






33. 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






34. 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






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






36. Some commonly used symbols for sample statistics






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






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






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 that part of a population which is actually observed.






41. 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






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






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






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






45. (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






46. 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)






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






48. 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.






49. Is a subset of the sample space - to which a probability can be assigned. For example - on rolling a die - 'getting a five or a six' is an event (with a probability of one third if the die is fair).






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