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






2. When you have two or more competing models - choose the simpler of the two models.






3. 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.






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






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






6. Given two jointly distributed random variables X and Y - the marginal distribution of X is simply the probability distribution of X ignoring information about Y.






7. Cov[X - Y] :






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






9. 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.






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






11. Any specific experimental condition applied to the subjects






12. Some commonly used symbols for population parameters






13. ?






14. The standard deviation of a sampling distribution.






15.






16. Failing to reject a false null hypothesis.






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






18. A variable has a value or numerical measurement for which operations such as addition or averaging make sense.






19. A measurement such that the random error is small






20. 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






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. 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.






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






24. 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.






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






26. 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.






27. The errors - or difference between the estimated response y^i and the actual measured response yi - collectively






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






29. 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.






30. A subjective estimate of probability.






31. 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






32. 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






33. Patterns in the data may be modeled in a way that accounts for randomness and uncertainty in the observations - and are then used for drawing inferences about the process or population being studied; this is called






34. (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.






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






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






37. 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.






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






39. 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.






40. S^2






41. Is a function that gives the probability of all elements in a given space: see List of probability distributions






42. 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






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






44. A group of individuals sharing some common features that might affect the treatment.






45. (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






46. Probability of rejecting a true null hypothesis.






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






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






49. 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






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