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






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






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






4. 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






5. 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






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






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






8. 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.






9. Another name for elementary event.






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






11. 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






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






13. 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






14. 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.






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






16. 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.






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






18. 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.






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






20. 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






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






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






23. Cov[X - Y] :






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






25. 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






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






27. 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.






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






29. Probability of accepting a false null hypothesis.






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






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






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






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






34. 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






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






36. 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.






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






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






39. Rejecting a true null hypothesis.






40. Any specific experimental condition applied to the subjects






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






42. A scale that represents an ordinal scale such as looks on a scale from 1 to 10.






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






44. 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.






45. 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}.






46. 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.






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






48. Is a sample and the associated data points.






49. 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






50. Samples are drawn from two different populations such that the sample data drawn from one population is completely unrelated to the selection of sample data from the other population.