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






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






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






4. Descriptive statistics and inferential statistics (a.k.a. - predictive statistics) together comprise






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






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






7. 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.






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






9. 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.






10. Data are gathered and correlations between predictors and response are investigated.






11. 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.






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






13. Cov[X - Y] :






14. 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






15. 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






16. 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






17. 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.






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






19. 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).






20. A numerical measure that describes an aspect of a population.






21. E[X] :






22. Rejecting a true null hypothesis.






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






24. 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.






25. 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






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






27. 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.






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






29. When there is an even number of values...






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






31. 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.






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






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






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. 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.






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






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






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






40. 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






41. Some commonly used symbols for sample statistics






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






43. 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






44. 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.






45. 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}.






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






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






48. 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.






49.






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







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