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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. 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






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






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






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






5. Some commonly used symbols for sample statistics






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






7.






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






9. 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)






10. (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






11. 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.






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






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






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






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






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






17. 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).






18. A variable has a value or numerical measurement for which operations such as addition or averaging make sense.






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






20. Where the null hypothesis fails to be rejected and an actual difference between populations is missed giving a 'false negative'.






21. Is the probability distribution - under repeated sampling of the population - of a given statistic.






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






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






24. 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.






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






26. The result of a Bayesian analysis that encapsulates the combination of prior beliefs or information with observed data






27. 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.






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






29. (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.






30. In the long run - as the sample size increases - the relative frequencies of outcomes approach to the theoretical probability.






31. 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.






32. ?






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






34. Some commonly used symbols for population parameters






35. 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.






36. When there is an even number of values...






37. 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






38. (cdfs) are denoted by upper case letters - e.g. F(x).






39. 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.






40. 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.






41. 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.






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






43. 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.






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






45. 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.






46. Are two related but separate academic disciplines. Statistical analysis often uses probability distributions - and the two topics are often studied together. However - probability theory contains much that is of mostly of mathematical interest and no






47. 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






48. Is a typed measurement - it can be a boolean value - a real number - a vector (in which case it's also called a data vector) - etc.






49. Another name for elementary event.






50. Samples are drawn from two different populations such that there is a matching of the first sample data drawn and a corresponding data value in the second sample data.