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






2. Rejecting a true null hypothesis.






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






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






5.






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






7. 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






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






9. 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






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






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






12. 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






13. A measure that is relevant or appropriate as a representation of that property.






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






15. 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.






16. 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.






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






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






19. 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






20. Is a sample and the associated data points.






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






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






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






24. Probability of rejecting a true null hypothesis.






25. 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'






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






27. Probability of accepting a false null hypothesis.






28. ?






29. Cov[X - Y] :






30. 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.






31. 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






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






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






34. A measurement such that the random error is small






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






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






37. 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






38. 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.






39. 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.






40. 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.






41. Var[X] :






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






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






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






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






46. 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






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






48. A numerical measure that describes an aspect of a sample.






49. (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






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