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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 length of the smallest interval which contains all the data.






2. 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






3. 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)






4. E[X] :






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






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






7. 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






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






9. 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.






10. A measure that is relevant or appropriate as a representation of that property.






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






12. 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.






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






14. To find the median value of a set of numbers: Arrange the numbers in numerical order. Locate the two middle numbers in the list. Find the average of those two middle values.






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






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






17. (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.






18. Cov[X - Y] :






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






20. 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.






21. 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






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






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






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






25. Another name for elementary event.






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






27. 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






28. 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






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






30. 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






31. Failing to reject a false null hypothesis.






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






33. A collection of events is mutually independent if for any subset of the collection - the joint probability of all events occurring is equal to the product of the joint probabilities of the individual events. Think of the result of a series of coin-fl






34. 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).






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






36. Uses patterns in the sample data to draw inferences about the population represented - accounting for randomness. These inferences may take the form of: answering yes/no questions about the data (hypothesis testing) - estimating numerical characteris






37. Are two related but separate academic disciplines. Statistical analysis often uses probability distributions - and the two topics are often studied together. However - probability theory contains much that is of mostly of mathematical interest and no






38. 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.






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






40. A subjective estimate of probability.






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






42. 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.






43. Is denoted by - pronounced 'x bar'.






44. (or just likelihood) is a conditional probability function considered a function of its second argument with its first argument held fixed. For example - imagine pulling a numbered ball with the number k from a bag of n balls - numbered 1 to n. Then






45. 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.






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






47. Some commonly used symbols for population parameters






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






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






50. 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.