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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. Is often denoted by placing a caret over the corresponding symbol - e.g. - pronounced 'theta hat'.






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






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






4. 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.






5. The errors - or difference between the estimated response y^i and the actual measured response yi - collectively






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






7. 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'






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






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






10. 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






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






12. Gives the probability distribution for a continuous random variable.






13. Another name for elementary event.






14. 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.






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






16. 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






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






18. (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






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






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






21. 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






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






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






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






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






26. Rejecting a true null hypothesis.






27. Cov[X - Y] :






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






29. 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.






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






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






32. 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.






33. 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






34. When there is an even number of values...






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






36. 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






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






38. 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






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






40. 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.






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






42. S^2






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






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






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






46. 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






47. Statistical methods can be used for summarizing or describing a collection of data; this is called






48. 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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49. 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.






50. (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.