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






2. Can refer either to a sample not being representative of the population - or to the difference between the expected value of an estimator and the true value.






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






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






5. 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.






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






7. 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.






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






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






10. Is used to describe probability in a continuous probability distribution. For example - you can't say that the probability of a man being six feet tall is 20% - but you can say he has 20% of chances of being between five and six feet tall. Probabilit






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






13. Describes the spread in the values of the sample statistic when many samples are taken.






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






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






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






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






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






19. 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






20. Failing to reject a false null hypothesis.






21. 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.






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






23. When info. in a contingency table is re-organized into more or less categories - relationships seen can change or reverse.

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24. 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.






25. 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






26. 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.






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






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






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






30. 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






31. 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'






32. 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.






33. (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






34. (e.g. ? - b) are commonly used to denote unknown parameters (population parameters).






35. (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.






36. 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






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






38. Probability of rejecting a true null hypothesis.






39. ?r






40. Data are gathered and correlations between predictors and response are investigated.






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






42. Are usually written with upper case calligraphic (e.g. F for the set of sets on which we define the probability P)






43. Some commonly used symbols for population parameters






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






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






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






47. Have no meaningful rank order among values.






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






49.






50. 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.