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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. ?r






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






3. Any specific experimental condition applied to the subjects






4. 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.






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






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






7. Can refer either to a sample not being representative of the population - or to the difference between the expected value of an estimator and the true value.






8. 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'






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






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






11. 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.






12. Statistical methods can be used for summarizing or describing a collection of data; this is called






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






14. 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






15. 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.






16. 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}.






17. (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






18. 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






19. Consists of a number of independent trials repeated under identical conditions. On each trial - there are two possible outcomes.






20. 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.






21. 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.






22. 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.


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






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






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






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






27. 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






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






29. 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.






30. The probability of correctly detecting a false null hypothesis.






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






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






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






34. 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






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






36. Rejecting a true null hypothesis.






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






38. 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






39. Failing to reject a false null hypothesis.






40. 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.






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






42. Have no meaningful rank order among values.






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






44. 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






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






46. 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)






47. 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






48. (also called statistical variability) is a measure of how diverse some data is. It can be expressed by the variance or the standard deviation.






49. Probability of rejecting a true null hypothesis.






50. 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.