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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. 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.






2. 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.






3. 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.






4. 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






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






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






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






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






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






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






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






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






15. 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






16. Have no meaningful rank order among values.






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






18. Var[X] :






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






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






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






22. 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.






23. 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.






24. 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'






25. 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.






26. 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).






27. Probability of rejecting a true null hypothesis.






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






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






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






31. Two variables such that their effects on the response variable cannot be distinguished from each other.






32. Some commonly used symbols for population parameters






33. 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.






34. Ratio and interval measurements which can be either discrete or continuous - due to their numerical nature are grouped together as






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






36. 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.






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






38. ?






39. A subjective estimate of probability.






40. Statistical methods can be used for summarizing or describing a collection of data; this is called






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






42. 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






43. Failing to reject a false null hypothesis.






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






45. 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






46. ?r






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






48. 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.






49. Another name for elementary event.






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