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CLEP General Mathematics: Probability And Statistics

Subjects : clep, math
Instructions:
  • Answer 50 questions in 15 minutes.
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  • Match each statement with the correct term.
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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. Gives the probability of events in a probability space.






2. Probability of rejecting a true null hypothesis.






3. Any specific experimental condition applied to the subjects






4. 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.






5. 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






6. 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.






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






8. 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






9. Involves taking measurements of the system under study - manipulating the system - and then taking additional measurements using the same procedure to determine if the manipulation has modified the values of the measurements.






10. (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






11. 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.






12. Used to reduce bias - this measure weights the more relevant information higher than less relevant info.






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






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






15. Another name for elementary event.






16. 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.






17. 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.






18. 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.






19. 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.






20. Rejecting a true null hypothesis.






21. 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).






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






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






24. 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






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






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






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






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






29. 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






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






31. ?






32. 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'






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






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






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






36. 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






37. Probability of accepting a false null hypothesis.






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






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






40. The standard deviation of a sampling distribution.






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






42. 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.






43. 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






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






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






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






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






48. 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






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






50. 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.







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