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 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}.






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






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

Warning: Invalid argument supplied for foreach() in /var/www/html/basicversity.com/show_quiz.php on line 183


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






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






6. The probability distribution of a sample statistic based on all the possible simple random samples of the same size from a population.






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






8. 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.






9. Another name for elementary event.






10. 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






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






12.






13. Describes a characteristic of an individual to be measured or observed.






14. Where the null hypothesis is falsely rejected giving a 'false positive'.






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






16. The standard deviation of a sampling distribution.






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






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






19. 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.






20. 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






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






22. Probability of accepting a false null hypothesis.






23. Is its expected value. The mean (or sample mean of a data set is just the average value.






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






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






26. 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.






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






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






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






30. 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.






31. E[X] :






32. 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






33. A subjective estimate of probability.






34. 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






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






36. ?r






37. S^2






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






39. 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.






40. 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.






41. 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






42. 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.






43. 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






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






45. 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.

Warning: Invalid argument supplied for foreach() in /var/www/html/basicversity.com/show_quiz.php on line 183


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






47. 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.






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






49. Have no meaningful rank order among values.






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