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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. ?r






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






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






4. 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.






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






6. 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}.






7. Var[X] :






8. Some commonly used symbols for sample statistics






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






10. 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






11. 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






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






13. 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.






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






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






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






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






18. 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






19. 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'






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






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






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






23. 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






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






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






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






27. Is the probability of two events occurring together. The joint probability of A and B is written P(A and B) or P(A - B).






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






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. 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






31. 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)






32. Long-term upward or downward movement over time.






33. The probability of correctly detecting a false null hypothesis.






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






35. ?






36. A measurement such that the random error is small






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






38. A subjective estimate of probability.






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






40. 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.






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






42. 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






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






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






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






46. 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






47. (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






48. Gives the probability of events in a probability space.






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






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







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