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. A numerical measure that assesses the strength of a linear relationship between two variables.






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






3. 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)






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






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






6. When there is an even number of values...






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






8. E[X] :






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






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






11. 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.






12. 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






13. 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.






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






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






16. 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






17. 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.






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






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






20. Is a sample and the associated data points.






21. Rejecting a true null hypothesis.






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






23. 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.






24. Another name for elementary event.






25. 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.






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






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






28. 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'






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






30. Var[X] :






31. Are written in corresponding lower case letters. For example x1 - x2 - ... - xn could be a sample corresponding to the random variable X.






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






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






34. Statistics involve methods of organizing - picturing - and summarizing information from samples or population.






35. Probability of accepting a false null hypothesis.






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






37. 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.






38. 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






39. Is the exact middle value of a set of numbers Arrange the numbers in numerical order. Find the value in the middle of the list.






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






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






42. Have no meaningful rank order among values.






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






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






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






46. (or atomic event) is an event with only one element. For example - when pulling a card out of a deck - 'getting the jack of spades' is an elementary event - while 'getting a king or an ace' is not.






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






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






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






50. Is the probability distribution - under repeated sampling of the population - of a given statistic.