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






2. Cov[X - Y] :






3. Given two random variables X and Y - the joint distribution of X and Y is the probability distribution of X and Y together.






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






5. 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.






6. Any specific experimental condition applied to the subjects






7. In Bayesian inference - this represents prior beliefs or other information that is available before new data or observations are taken into account.






8. Some commonly used symbols for sample statistics






9. Failing to reject a false null hypothesis.






10. E[X] :






11. 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).






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






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






14. 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.






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






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






17. 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






18. S^2






19. Describes a characteristic of an individual to be measured or observed.






20. 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.






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






22. 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






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. Another name for elementary event.






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






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






27. 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






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

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






30. 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.






31. Var[X] :






32. 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






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






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






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






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






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






38. Is its expected value. The mean (or sample mean of a data set is just the average value.






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






40. 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'






41. 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






42. 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






43. 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.






44. 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.






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






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






47. (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






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






49.






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