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. 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






2. 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.






3. 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.






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






5. 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.






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






7. S^2






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






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






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






11. Var[X] :






12. 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






13. 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.






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






15. Is the probability of an event - ignoring any information about other events. The marginal probability of A is written P(A). Contrast with conditional probability.






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






17. 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


18. Cov[X - Y] :






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






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






21. Is a measure of the 'peakedness' of the probability distribution of a real-valued random variable. Higher kurtosis means more of the variance is due to infrequent extreme deviations - as opposed to frequent modestly sized deviations.






22. 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






23. A measurement such that the random error is small






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






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






26. 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






27. (or expectation) of a random variable is the sum of the probability of each possible outcome of the experiment multiplied by its payoff ('value'). Thus - it represents the average amount one 'expects' to win per bet if bets with identical odds are re






28. 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.






29. 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.






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






31. Is the study of the collection - organization - analysis - and interpretation of data. It deals with all aspects of this - including the planning of data collection in terms of the design of surveys and experiments.






32. 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}.






33. 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






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






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






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






37. 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






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






39. Are two related but separate academic disciplines. Statistical analysis often uses probability distributions - and the two topics are often studied together. However - probability theory contains much that is of mostly of mathematical interest and no






40. ?






41. Some commonly used symbols for population parameters






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






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






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






45. Some commonly used symbols for sample statistics






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






47. A collection of events is mutually independent if for any subset of the collection - the joint probability of all events occurring is equal to the product of the joint probabilities of the individual events. Think of the result of a series of coin-fl






48. 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.






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






50. 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.