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






2. Failing to reject a false null hypothesis.






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






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






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






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






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






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

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9. Cov[X - Y] :






10. 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






11. A subjective estimate of probability.






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






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






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






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






16. 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






17. The standard deviation of a sampling distribution.






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






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






20. 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.






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. There are four main levels of measurement used in statistics: Each of these have different degrees of usefulness in statistical research.






23. 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






24. S^2






25. Design of experiments - using blocking to reduce the influence of confounding variables - and randomized assignment of treatments to subjects to allow unbiased estimates of treatment effects and experimental error. At this stage - the experimenters a






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






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






28. ?






29. Is a sample space over which a probability measure has been defined.






30. 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.






31.






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






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






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






35. The probability of the observed value or something more extreme under the assumption that the null hypothesis is true.






36. 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.






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






38. 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}.






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






40. 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.






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






42. (or just likelihood) is a conditional probability function considered a function of its second argument with its first argument held fixed. For example - imagine pulling a numbered ball with the number k from a bag of n balls - numbered 1 to n. Then






43. 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






44. 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).






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






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






47. 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






48. Any specific experimental condition applied to the subjects






49. 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






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