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. 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.






2. Design of experiments - using blocking to reduce the influence of confounding variables - and randomized assignment of treatments to subjects to allow unbiased estimates of treatment effects and experimental error. At this stage - the experimenters a






3. Another name for elementary event.






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






5. Patterns in the data may be modeled in a way that accounts for randomness and uncertainty in the observations - and are then used for drawing inferences about the process or population being studied; this is called






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






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






8. Is inference about a population from a random sample drawn from it or - more generally - about a random process from its observed behavior during a finite period of time.






9. 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.






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






11. 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).






12. A list of individuals from which the sample is actually selected.






13. S^2






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






15. 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






16. Used to reduce bias - this measure weights the more relevant information higher than less relevant info.






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






18. 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}.






19. Performing the experiment following the experimental protocol and analyzing the data following the experimental protocol. 4. Further examining the data set in secondary analyses - to suggest new hypotheses for future study. 5. Documenting and present






20. Is data that can take only two values - usually represented by 0 and 1.






21. Have no meaningful rank order among values.






22. Probability of rejecting a true null hypothesis.






23. 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.






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






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






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






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






28. 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.






29. 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.






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






31. 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.






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






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






34. Because variables conforming only to nominal or ordinal measurements cannot be reasonably measured numerically - sometimes they are grouped together as






35. 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






36. 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.


37. Rejecting a true null hypothesis.






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






39. ?r






40. Is a process of selecting observations to obtain knowledge about a population. There are many methods to choose on which sample to do the observations.






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






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






43. 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.






44. A pairwise independent collection of random variables is a set of random variables any two of which are independent.






45. Any specific experimental condition applied to the subjects






46. 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.






47. Some commonly used symbols for sample statistics






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






49. 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'






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.