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






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






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






4. 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.






5. The objects described by a set of data: person (animal) - place - and - thing. (SUBJECTS)






6. Ratio and interval measurements which can be either discrete or continuous - due to their numerical nature are grouped together as






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






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






9. 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.






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






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






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






13. ?r






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






15. 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






16. Some commonly used symbols for sample statistics






17. Is the result of applying a statistical algorithm to a data set. It can also be described as an observable random variable.






18. The standard deviation of a sampling distribution.






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






20. Have no meaningful rank order among values.






21. 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






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






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






24. ?






25. Failing to reject a false null hypothesis.






26. Error also refers to the extent to which individual observations in a sample differ from a central value - such as






27. To prove the guiding theory further - these predictions are tested as well - as part of the scientific method. If the inference holds true - then the descriptive statistics of the new data increase the soundness of that






28. 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






29. Is a typed measurement - it can be a boolean value - a real number - a vector (in which case it's also called a data vector) - etc.






30. 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






31. (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






32. Cov[X - Y] :






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






34. 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.






35. 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.






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






37. S^2






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






39. Is the probability of some event A - assuming event B. Conditional probability is written P(A|B) - and is read 'the probability of A - given B'






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






41. 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.






42. 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.






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






44. 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.






45. Rejecting a true null hypothesis.






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






47. 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.






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






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






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