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






2. ?r






3. 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.






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






5. Is a parameter that indexes a family of probability distributions.






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






7. A subjective estimate of probability.






8. 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






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






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






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






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






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






14. Given two random variables X and Y - the joint distribution of X and Y is the probability distribution of X and Y together.






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






16. 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






17. Can refer either to a sample not being representative of the population - or to the difference between the expected value of an estimator and the true value.






18. The objects described by a set of data: person (animal) - place - and - thing. (SUBJECTS)






19. 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.






20. 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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21. 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






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






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






24. Is its expected value. The mean (or sample mean of a data set is just the average value.






25. Is the exact middle value of a set of numbers Arrange the numbers in numerical order. Find the value in the middle of the list.






26. 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).






27. S^2






28. 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)






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






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






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






32. 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






33. The standard deviation of a sampling distribution.






34. Some commonly used symbols for sample statistics






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






36. A measurement such that the random error is small






37. The probability of correctly detecting a false null hypothesis.






38. 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}.






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






40. 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






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






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






43. (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






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






45. 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.






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






47. When info. in a contingency table is re-organized into more or less categories - relationships seen can change or reverse.

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






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






50. 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