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






2. Var[X] :






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






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






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






6. 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).






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






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






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






10. 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






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






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






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






14. Have no meaningful rank order among values.






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






16. 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.






17. Can be - for example - the possible outcomes of a dice roll (but it is not assigned a value). The distribution function of a random variable gives the probability of different results. We can also derive the mean and variance of a random variable.






18. 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.






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






20. 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






21. A measurement such that the random error is small






22. 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






23. 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






24. (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






25. 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






26. A group of individuals sharing some common features that might affect the treatment.






27. 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






28. A list of individuals from which the sample is actually selected.






29. Another name for elementary event.






30. 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






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






32. Are usually written in upper case roman letters: X - Y - etc.






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






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






35. Because variables conforming only to nominal or ordinal measurements cannot be reasonably measured numerically - sometimes they are grouped together as






36. 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.






37. 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).






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






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






40. Many statistical methods seek to minimize the mean-squared error - and these are called






41. In the long run - as the sample size increases - the relative frequencies of outcomes approach to the theoretical probability.






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






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






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






45. Is the length of the smallest interval which contains all the data.






46. 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.






47. 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.






48. 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






49. 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.






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