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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. 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






2. 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






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






4. Another name for elementary event.






5. 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.






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






7. 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






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






9. 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






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






11. 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.






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






13. 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.






14. 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.






15. A consistent - repeated deviation of the sample statistic from the population parameter in the same direction when many samples are taken.






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






17. 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.






18. Probability of rejecting a true null hypothesis.






19. 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.






20. Any specific experimental condition applied to the subjects






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






22. 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'






23. ?






24. Gives the probability distribution for a continuous random variable.






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






26. A measurement such that the random error is small






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






28. E[X] :






29. 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.






30. The standard deviation of a sampling distribution.






31. Long-term upward or downward movement over time.






32. (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






33. 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.






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






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


36. 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.






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






38. 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.


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






40. Have meaningful distances between measurements defined - but the zero value is arbitrary (as in the case with longitude and temperature measurements in Celsius or Fahrenheit)






41. Have both a meaningful zero value and the distances between different measurements defined; they provide the greatest flexibility in statistical methods that can be used for analyzing the data






42. 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.






43. 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.






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






45. Rejecting a true null hypothesis.






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






47. 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.






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






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






50. Because variables conforming only to nominal or ordinal measurements cannot be reasonably measured numerically - sometimes they are grouped together as