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






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






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






4. (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






5. Is a function that gives the probability of all elements in a given space: see List of probability distributions






6. 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.






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






8. 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.






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






10. 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.






11. Ratio and interval measurements which can be either discrete or continuous - due to their numerical nature are grouped together as






12. 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






13. Is one that explores the correlation between smoking and lung cancer. This type of study typically uses a survey to collect observations about the area of interest and then performs statistical analysis. In this case - the researchers would collect o






14. E[X] :






15. 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.






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






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






18. 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.






19. S^2






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






21. 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






22. 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.






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






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






25. 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}.






26. 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.






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






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

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29. 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.






30. 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






31. 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'






32. 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.

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






34. Is the result of applying a statistical algorithm to a data set. It can also be described as an observable random variable.






35. 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.






36. Is a typed measurement - it can be a boolean value - a real number - a vector (in which case it's also called a data vector) - etc.






37. 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)






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






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






40. Probability of rejecting a true null hypothesis.






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






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






43. Summarize the population data by describing what was observed in the sample numerically or graphically. Numerical descriptors include mean and standard deviation for continuous data types (like heights or weights) - while frequency and percentage are






44. Another name for elementary event.






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






46.






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






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






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






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