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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. 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.






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






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






4. Many statistical methods seek to minimize the mean-squared error - and these are called






5. S^2






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






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






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






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






10. The standard deviation of a sampling distribution.






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






12. 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}.






13. Failing to reject a false null hypothesis.






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






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






16. Some commonly used symbols for sample statistics






17. 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.






18. 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.






19. A subjective estimate of probability.






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






21. Is data arising from counting that can take only non-negative integer values.






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






23. Probability of accepting a false null hypothesis.






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






25. 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






26. 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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27. 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.






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






29. Is the probability of two events occurring together. The joint probability of A and B is written P(A and B) or P(A - B).






30. 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.






31. 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






32. ?






33. 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.






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






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






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






37. (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.






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






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






40. 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.






41. Is the length of the smallest interval which contains all the data.






42. A measurement such that the random error is small






43. 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






44. 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).






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






46. 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






47. Any specific experimental condition applied to the subjects






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






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






50. 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)