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CLEP General Mathematics: Probability And Statistics

Subjects : clep, math
Instructions:
  • Answer 50 questions in 15 minutes.
  • If you are not ready to take this test, you can study here.
  • Match each statement with the correct term.
  • Don't refresh. All questions and answers are randomly picked and ordered every time you load a test.

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






2. 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.






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






4. 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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5. When there is an even number of values...






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






7. 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.






8. 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






9. 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






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






11. 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.






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






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






14. 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.






15. Is the probability of some event A - assuming event B. Conditional probability is written P(A|B) - and is read 'the probability of A - given B'






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






17. 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.






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






19. 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.






20. 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.






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






22. Another name for elementary event.






23. 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.






24. 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.






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






26. 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






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






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






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






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






31. 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






32. (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.






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






34. 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.






35. Have no meaningful rank order among values.






36. Is a measure of the 'peakedness' of the probability distribution of a real-valued random variable. Higher kurtosis means more of the variance is due to infrequent extreme deviations - as opposed to frequent modestly sized deviations.






37. Any specific experimental condition applied to the subjects






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






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






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






42. 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.






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






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






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






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






47. Some commonly used symbols for population parameters






48. The probability distribution of a sample statistic based on all the possible simple random samples of the same size from a population.






49. 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.






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