Test your basic knowledge |

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. 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.






2. 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.






3. 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






4. 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.






5. 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.






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






7. ?r






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






9. Is a sample and the associated data points.






10. Cov[X - Y] :






11. 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.

Warning: Invalid argument supplied for foreach() in /var/www/html/basicversity.com/show_quiz.php on line 183


12. 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).






13. Rejecting a true null hypothesis.






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






15. 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.






16. 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






17. 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.






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






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






20. A measurement such that the random error is small






21. S^2






22. 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






23. The standard deviation of a sampling distribution.






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






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






26. E[X] :






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






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






29. Have no meaningful rank order among values.






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






31. Probability of accepting a false null hypothesis.






32. Some commonly used symbols for sample statistics






33. (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.






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






35. 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.






36.






37. 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






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






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






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






42. Another name for elementary event.






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






44. 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.






45. Failing to reject a false null hypothesis.






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






47. Any specific experimental condition applied to the subjects






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






49. 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.






50. 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.