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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. 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






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






3. 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






4. 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






5. A numerical facsimilie or representation of a real-world phenomenon.






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






7. 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.






8. Cov[X - Y] :






9. 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.






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






11. 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.






12. 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.






13. Occurs when a subject receives no treatment - but (incorrectly) believes he or she is in fact receiving treatment and responds favorably.






14. 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.






15. A pairwise independent collection of random variables is a set of random variables any two of which are independent.






16. A data value that falls outside the overall pattern of the graph.






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






18. Is a sample space over which a probability measure has been defined.






19. 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






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






21. Some commonly used symbols for population parameters






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






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






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






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






26. 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}.






27. 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






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






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






30. 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.






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. 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).






33. 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






34. 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.






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






36. 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.






37. 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






38. Any specific experimental condition applied to the subjects






39. A measurement such that the random error is small






40. S^2






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






42. 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






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






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






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






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






47. 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.






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






49. Have meaningful distances between measurements defined - but the zero value is arbitrary (as in the case with longitude and temperature measurements in Celsius or Fahrenheit)






50. 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