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






2. Many statistical methods seek to minimize the mean-squared error - and these are called






3. 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.






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






5. 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






6. ?






7. ?r






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






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






11. 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.






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






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






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






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






16. Planning the research - including finding the number of replicates of the study - using the following information: preliminary estimates regarding the size of treatment effects - alternative hypotheses - and the estimated experimental variability. Co






17. 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'






18. 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.






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






20. Some commonly used symbols for population parameters






21. Is one that explores the correlation between smoking and lung cancer. This type of study typically uses a survey to collect observations about the area of interest and then performs statistical analysis. In this case - the researchers would collect o






22. Is used in 'mathematical statistics' (alternatively - 'statistical theory') to study the sampling distributions of sample statistics and - more generally - the properties of statistical procedures. The use of any statistical method is valid when the






23. Is denoted by - pronounced 'x bar'.






24. 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.






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






26. 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






27. Where the null hypothesis fails to be rejected and an actual difference between populations is missed giving a 'false negative'.






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






29. Failing to reject a false null hypothesis.






30.






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






32. 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






33. Is a subset of the sample space - to which a probability can be assigned. For example - on rolling a die - 'getting a five or a six' is an event (with a probability of one third if the die is fair).






34. 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.






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






36. Is the probability distribution - under repeated sampling of the population - of a given statistic.






37. Statistics involve methods of using information from a sample to draw conclusions regarding the population.






38. 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.






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






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






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






42. 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.






43. 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.






44. 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.






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






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






47. A measurement such that the random error is small






48. (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






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






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