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






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






3. 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.






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






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






6. 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






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






8. (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






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






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






11. 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)






12. 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.


13. Is the exact middle value of a set of numbers Arrange the numbers in numerical order. Find the value in the middle of the list.






14. 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.






15. A numerical facsimilie or representation of a real-world phenomenon.






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






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






18. Any specific experimental condition applied to the subjects






19. Are simply two different terms for the same thing. Add the given values






20. 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






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






22. Var[X] :






23. 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.






24. 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.






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






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






27. Some commonly used symbols for sample statistics






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






29. 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.






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






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






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






33. Data are gathered and correlations between predictors and response are investigated.






34. 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.






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


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






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






38. Occurs when a subject receives no treatment - but (incorrectly) believes he or she is in fact receiving treatment and responds favorably.






39. 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






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






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






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






43. 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






44. When there is an even number of values...






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






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






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






48. 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.






49. Have no meaningful rank order among values.






50. ?r