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






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






3. 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.






4. Where the null hypothesis fails to be rejected and an actual difference between populations is missed giving a 'false negative'.






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






6. A subjective estimate of probability.






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






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






9. 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.






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






11. 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}.






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






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. The probability distribution of a sample statistic based on all the possible simple random samples of the same size from a population.






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






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






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






18. A measurement such that the random error is small






19. 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.






20. Is used in 'mathematical statistics' (alternatively - 'statistical theory') to study the sampling distributions of sample statistics and - more generally - the properties of statistical procedures. The use of any statistical method is valid when the






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






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






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






24. (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






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






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






27. 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






28. 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






29. 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.






30. 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.






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






32. Is defined as the expected value of random variable (X -






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






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






35. 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






36. 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






37. 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






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






39. 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.






40. Another name for elementary event.






41. Given two random variables X and Y - the joint distribution of X and Y is the probability distribution of X and Y together.






42. 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.






43. 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.






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






45. 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






46. 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.






47. Failing to reject a false null hypothesis.






48. 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






49. 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.






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