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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 that part of a population which is actually observed.






2. Is a sample and the associated data points.






3. Design of experiments - using blocking to reduce the influence of confounding variables - and randomized assignment of treatments to subjects to allow unbiased estimates of treatment effects and experimental error. At this stage - the experimenters a






4. To find the average - or arithmetic mean - of a set of numbers:






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






6. (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.






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






8. 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.






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






10. 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.






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






12. E[X] :






13. The probability of correctly detecting a false null hypothesis.






14. S^2






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






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






17. 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.






18. 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).






19. Rejecting a true null hypothesis.






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






21. 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






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






23. (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






24. (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






25. 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.






26. Probability of accepting a false null hypothesis.






27. 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.






28. Cov[X - Y] :






29. 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






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






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






32. 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






33. ?






34. Patterns in the data may be modeled in a way that accounts for randomness and uncertainty in the observations - and are then used for drawing inferences about the process or population being studied; this is called






35. Is the function that gives the probability distribution of a random variable. It cannot be negative - and its integral on the probability space is equal to 1.






36. Is the probability of some event A - assuming event B. Conditional probability is written P(A|B) - and is read 'the probability of A - given B'






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






38. Data are gathered and correlations between predictors and response are investigated.






39. Any specific experimental condition applied to the subjects






40. 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






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






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






43. Some commonly used symbols for sample statistics






44. Another name for elementary event.






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






46. 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






47. 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






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






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






50. Is data arising from counting that can take only non-negative integer values.