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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. 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.






2. Var[X] :






3. Another name for elementary event.






4. Is that part of a population which is actually observed.






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






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






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






8. 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.






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






10. 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.






11. 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






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






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






15. To prove the guiding theory further - these predictions are tested as well - as part of the scientific method. If the inference holds true - then the descriptive statistics of the new data increase the soundness of that






16. Some commonly used symbols for sample statistics






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






18. Error also refers to the extent to which individual observations in a sample differ from a central value - such as






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






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






21. Have imprecise differences between consecutive values - but have a meaningful order to those values






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






23. 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.






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






25. (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






26. Is a sample and the associated data points.






27. 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.






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






29. Is a function of the known data that is used to estimate an unknown parameter; an estimate is the result from the actual application of the function to a particular set of data. The mean can be used as an estimator.






30. 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






31. 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).






32. Is the most commonly used measure of statistical dispersion. It is the square root of the variance - and is generally written s (sigma).






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






34. 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.






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






36. 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.






37. 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






38. Statistics involve methods of organizing - picturing - and summarizing information from samples or population.






39. Is often denoted by placing a caret over the corresponding symbol - e.g. - pronounced 'theta hat'.






40. Cov[X - Y] :






41. 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.






42. Are written in corresponding lower case letters. For example x1 - x2 - ... - xn could be a sample corresponding to the random variable X.






43. 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.


44. (or atomic event) is an event with only one element. For example - when pulling a card out of a deck - 'getting the jack of spades' is an elementary event - while 'getting a king or an ace' is not.






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






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






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






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






49. In number theory - scatter plots of data generated by a distribution function may be transformed with familiar tools used in statistics to reveal underlying patterns - which may then lead to






50. A subjective estimate of probability.