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. Describes the spread in the values of the sample statistic when many samples are taken.






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






3. 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.






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






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






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






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






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






9. The probability of the observed value or something more extreme under the assumption that the null hypothesis is true.






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






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






12. 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.






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






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






15. To prove the guiding theory further - these predictions are tested as well - as part of the scientific method. If the inference holds true - then the descriptive statistics of the new data increase the soundness of that






16. 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.






17. 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)






18. 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.






19. 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.






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






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






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






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






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






25. ?r






26. 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.






27. Is a sample and the associated data points.






28. Var[X] :






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






30. Another name for elementary event.






31. 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


32. Some commonly used symbols for sample statistics






33. 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.






34. 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


35. 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






36. 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






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






38. Failing to reject a false null hypothesis.






39. Interpretation of statistical information in that the assumption is that whatever is proposed as a cause has no effect on the variable being measured can often involve the development of a






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






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






42. 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.






43. A scale that represents an ordinal scale such as looks on a scale from 1 to 10.






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






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






46. Statistics involve methods of using information from a sample to draw conclusions regarding the population.






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






48. Also called correlation coefficient - is a numeric measure of the strength of linear relationship between two random variables (one can use it to quantify - for example - how shoe size and height are correlated in the population). An example is the P






49. A sample selected in such a way that each individual is equally likely to be selected as well as any group of size n is equally likely to be selected.






50. 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.