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CLEP General Mathematics: Probability And Statistics

Subjects : clep, math
Instructions:
  • Answer 50 questions in 15 minutes.
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  • Match each statement with the correct term.
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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. Some commonly used symbols for sample statistics






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






3. 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.






4. 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.






5. 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'






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






7. (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.






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






9. Error also refers to the extent to which individual observations in a sample differ from a central value - such as






10. 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






11. A measurement such that the random error is small






12. Rejecting a true null hypothesis.






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






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






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






16. Is a measure of the asymmetry of the probability distribution of a real-valued random variable. Roughly speaking - a distribution has positive skew (right-skewed) if the higher tail is longer and negative skew (left-skewed) if the lower tail is longe






17. 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






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






19. 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.






20. (pdfs) and probability mass functions are denoted by lower case letters - e.g. f(x).






21. 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






22. 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.






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






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






25. 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.






26. 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.






27. Involves taking measurements of the system under study - manipulating the system - and then taking additional measurements using the same procedure to determine if the manipulation has modified the values of the measurements.






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






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






30. 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






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






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






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






34. 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.






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






36. 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






37. Is the result of applying a statistical algorithm to a data set. It can also be described as an observable random variable.






38. Can be a population parameter - a distribution parameter - an unobserved parameter (with different shades of meaning). In statistics - this is often a quantity to be estimated.

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






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






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






43. 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






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






45. ?r






46. 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






47. Is the set of possible outcomes of an experiment. For example - the sample space for rolling a six-sided die will be {1 - 2 - 3 - 4 - 5 - 6}.






48. Another name for elementary event.






49. Cov[X - Y] :






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