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






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






4. 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






5. 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






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






7. There are four main levels of measurement used in statistics: Each of these have different degrees of usefulness in statistical research.






8. 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.






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






10. 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






11. 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






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






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






14. 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.






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






16. 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.






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






18. ?






19. 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.






20. 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.






21. Are written in corresponding lower case letters. For example x1 - x2 - ... - xn could be a sample corresponding to the random variable X.






22. 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.






23. The standard deviation of a sampling distribution.






24. 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






25. Probability of rejecting a true null hypothesis.






26. 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.






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






28. 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






29. 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.






30. Rejecting a true null hypothesis.






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






32. Is a sample and the associated data points.






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






34. 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






35. 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.






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






37. 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






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






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






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






41. Var[X] :






42. Probability of accepting a false null hypothesis.






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






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






45. Is used to describe probability in a continuous probability distribution. For example - you can't say that the probability of a man being six feet tall is 20% - but you can say he has 20% of chances of being between five and six feet tall. Probabilit






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






47. S^2






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






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






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







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