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 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






2. Planning the research - including finding the number of replicates of the study - using the following information: preliminary estimates regarding the size of treatment effects - alternative hypotheses - and the estimated experimental variability. Co






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






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






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






6. E[X] :






7. Uses patterns in the sample data to draw inferences about the population represented - accounting for randomness. These inferences may take the form of: answering yes/no questions about the data (hypothesis testing) - estimating numerical characteris






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






9. Failing to reject a false null hypothesis.






10. (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.






11. 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






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






13. 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






14. Are usually written with upper case calligraphic (e.g. F for the set of sets on which we define the probability P)






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






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






17. 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.






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






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






20. 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.






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






22. Working from a null hypothesis two basic forms of error are recognized:






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






24. Probability of rejecting a true null hypothesis.






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






26. Is a set of entities about which statistical inferences are to be drawn - often based on random sampling. One can also talk about a population of measurements or values.






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






28. 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.






29. Have no meaningful rank order among values.






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






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






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






34. 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.






35. 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.






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






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






38. 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}.






39. 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






40. Cov[X - Y] :






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






42. Are simply two different terms for the same thing. Add the given values






43. 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






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






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






46. 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






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






48. 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






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






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