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






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






3. 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






4. 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.






5. 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






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






7. Is often denoted by placing a caret over the corresponding symbol - e.g. - pronounced 'theta hat'.






8. 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.






9. (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






10. The collection of all possible outcomes in an experiment.






11. 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).






12. Probability of rejecting a true null hypothesis.






13. 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.






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






15. Is a process of selecting observations to obtain knowledge about a population. There are many methods to choose on which sample to do the observations.






16. Cov[X - Y] :






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






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






19. 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'






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






21. Statistics involve methods of organizing - picturing - and summarizing information from samples or population.






22. 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






23. 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.






24. 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.






25. 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






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






27. Any specific experimental condition applied to the subjects






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






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






30. 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.






31. (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






32. A collection of events is mutually independent if for any subset of the collection - the joint probability of all events occurring is equal to the product of the joint probabilities of the individual events. Think of the result of a series of coin-fl






33. Is inference about a population from a random sample drawn from it or - more generally - about a random process from its observed behavior during a finite period of time.






34.






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






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






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






38. 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






39. 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.






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






41. ?r






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






43. 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.






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






45. 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.






46. The proportion of the explained variation by a linear regression model in the total variation.






47. The probability of the observed value or something more extreme under the assumption that the null hypothesis is true.






48. 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.






49. Probability of accepting a false null hypothesis.






50. 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