Test your basic knowledge |

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 probability of some event A - assuming event B. Conditional probability is written P(A|B) - and is read 'the probability of A - given B'






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






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






4. Probability of rejecting a true null hypothesis.






5. ?r






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






7. Is that part of a population which is actually observed.






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






9. Rejecting a true null hypothesis.






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






11. 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.






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






13. 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






14. 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






15. A variable describes an individual by placing the individual into a category or a group.






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






17. 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.






18. Given two jointly distributed random variables X and Y - the marginal distribution of X is simply the probability distribution of X ignoring information about Y.






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






20. 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).






21. 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.






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






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






24. 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.






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






26. Gives the probability of events in a probability space.






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






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






29. Two events are independent if the outcome of one does not affect that of the other (for example - getting a 1 on one die roll does not affect the probability of getting a 1 on a second roll). Similarly - when we assert that two random variables are i






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






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






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






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






34. Some commonly used symbols for sample statistics






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






36. Have no meaningful rank order among values.






37. 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






38. 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).






39. 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.






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






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






42. A measurement such that the random error is small






43. A numerical measure that describes an aspect of a sample.






44. (or multivariate random variable) is a vector whose components are random variables on the same probability space.






45. ?






46. 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






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






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






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






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






Can you answer 50 questions in 15 minutes?



Let me suggest you:

Browse all subjects

Browse all tests

Most popular tests



Major Subjects

Tests & Exams


AP
CLEP
DSST
GRE
SAT
GMAT

Browse all subjects

Browse all tests

Most popular tests