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






2. Any specific experimental condition applied to the subjects






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






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






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






6. 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.






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






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






9. Have no meaningful rank order among values.






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






11. 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.






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






13. The result of a Bayesian analysis that encapsulates the combination of prior beliefs or information with observed data






14. 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






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






16. 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






17. Can be a population parameter - a distribution parameter - an unobserved parameter (with different shades of meaning). In statistics - this is often a quantity to be estimated.

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






19. Is the study of the collection - organization - analysis - and interpretation of data. It deals with all aspects of this - including the planning of data collection in terms of the design of surveys and experiments.






20. Is data arising from counting that can take only non-negative integer values.






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






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






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






24. 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.






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






26. Probability of accepting a false null hypothesis.






27. 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






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






29. 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.






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






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






32. 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






33. 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.






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. Gives the probability of events in a probability space.






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






37. 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.






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






39. 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






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






41. 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






42. 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.






43. 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.






44. (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






45. 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)






46. 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






47. Some commonly used symbols for population parameters






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






49. (or atomic event) is an event with only one element. For example - when pulling a card out of a deck - 'getting the jack of spades' is an elementary event - while 'getting a king or an ace' is not.






50. (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







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