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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 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.






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






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






4. ?r






5. Any specific experimental condition applied to the subjects






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

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






9. Some commonly used symbols for population parameters






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






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






12. 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






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






14. Gives the probability of events in a probability space.






15. 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.






16. Var[X] :






17. 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.






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






19. 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.






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






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






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






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






24. Rejecting a true null hypothesis.






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






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






27. Changes over time that show a regular periodicity in the data where regular means over a fixed interval; the time between repetitions is called the period.






28. 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






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






30. 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.






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






32. 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.






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






34. 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.






35. Is a sample and the associated data points.






36. Given two jointly distributed random variables X and Y - the conditional probability distribution of Y given X (written 'Y | X') is the probability distribution of Y when X is known to be a particular value.






37. Some commonly used symbols for sample statistics






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






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






40. 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






41. 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.






42. 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






43. 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.






44. Have no meaningful rank order among values.






45. 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.






46. 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).






47. 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






48. E[X] :






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






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







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