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






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






3. 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}.






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






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






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






7. E[X] :






8. Have no meaningful rank order among values.






9. 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.






10. Is used to describe probability in a continuous probability distribution. For example - you can't say that the probability of a man being six feet tall is 20% - but you can say he has 20% of chances of being between five and six feet tall. Probabilit






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






12. 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.






13. 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






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






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






16. Some commonly used symbols for population parameters






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






18. 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.






19. A pairwise independent collection of random variables is a set of random variables any two of which are independent.






20. (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.






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






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






23. Is the probability of an event - ignoring any information about other events. The marginal probability of A is written P(A). Contrast with conditional probability.






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






25. 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.






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






27. In particular - the pdf of the standard normal distribution is denoted by






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






29. 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






30. Another name for elementary event.






31. Planning the research - including finding the number of replicates of the study - using the following information: preliminary estimates regarding the size of treatment effects - alternative hypotheses - and the estimated experimental variability. Co






32. 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






33. A subjective estimate of probability.






34. A list of individuals from which the sample is actually selected.






35. 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)






36. ?r






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






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






39. 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.






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






41. 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).






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






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






44. The collection of all possible outcomes in an experiment.






45. 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.






46. 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






47. The result of a Bayesian analysis that encapsulates the combination of prior beliefs or information with observed data






48. 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.






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






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