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






2. 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


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






4. 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.






5. Some commonly used symbols for sample statistics






6. 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






7. Rejecting a true null hypothesis.






8. 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


9. Is often denoted by placing a caret over the corresponding symbol - e.g. - pronounced 'theta hat'.






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






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






12. (or just likelihood) is a conditional probability function considered a function of its second argument with its first argument held fixed. For example - imagine pulling a numbered ball with the number k from a bag of n balls - numbered 1 to n. Then






13. Statistical methods can be used for summarizing or describing a collection of data; this is called






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






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






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






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






18. Probability of rejecting a true null hypothesis.






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






20. A measure that is relevant or appropriate as a representation of that property.






21. 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.






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






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






24. 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






25. S^2






26. 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






27. (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.






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






29. 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.






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. 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.






32. ?r






33. 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






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






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






36. 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






37. 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.






38. 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






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






40. Probability of accepting a false null hypothesis.






41. 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






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






43. Is a subset of the sample space - to which a probability can be assigned. For example - on rolling a die - 'getting a five or a six' is an event (with a probability of one third if the die is fair).






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






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






46. Failing to reject a false null hypothesis.






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






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






49. 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






50. 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