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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. 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






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






3. Cov[X - Y] :






4. ?






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






6. Where the null hypothesis is falsely rejected giving a 'false positive'.






7. 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.






8. 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






9. 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.






10. Two events are independent if the outcome of one does not affect that of the other (for example - getting a 1 on one die roll does not affect the probability of getting a 1 on a second roll). Similarly - when we assert that two random variables are i






11. A measurement such that the random error is small






12. 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






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






14. Have no meaningful rank order among values.






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






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






17. 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.






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






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






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






21. Have meaningful distances between measurements defined - but the zero value is arbitrary (as in the case with longitude and temperature measurements in Celsius or Fahrenheit)






22. 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






23. Probability of accepting a false null hypothesis.






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






25. 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.






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






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






28. 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






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






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






31. 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.






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






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






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






35. 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






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






37. In Bayesian inference - this represents prior beliefs or other information that is available before new data or observations are taken into account.






38. 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.






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






40. 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.






41. 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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42. Is a sample and the associated data points.






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






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






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






46. Are usually written with upper case calligraphic (e.g. F for the set of sets on which we define the probability P)






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






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






49. 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






50. Probability of rejecting a true null hypothesis.