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AP Statistics Vocab

Subjects : statistics, ap
Instructions:
  • Answer 50 questions in 15 minutes.
  • If you are not ready to take this test, you can study here.
  • 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. The square of the correlation between y and x; gives the fraction of the variability of y accounted for by the least squares linear regression on x; an overall measure of how successful the regression is in linearly relating y to x






2. The middle value with half of the data above and half below it






3. A distribution is this if it's not symmetric and one tail stretches out farther than the other






4. Displays the 5-number summary as a central box with whiskers that extend to the non-outlying data values






5. An arrangement of data in which each row represents a case and each column represents a variable






6. Shows the relationship between two quantitative variables measured on the same cases






7. Models random events by using random numbers to specify event outcomes with relative frequencies that correspond to the true real-world relative frequencies we are trying to model






8. The number of individuals in a sample






9. A representative subset of a population - examined in hope of learning about the population






10. Displays counts and - sometimes - percentages of individuals falling into named categories on two or more variables; categorizes the individuals on all variables at once - to reveal possible patterns in one variable that may be contingent on the cate






11. In a normal model - about 68% of values fall within 1 standard deviation of the mean - about 95% fall within 2 standard deviations of the mean - and about 99.7% fall within 3 standard deviations of the mean






12. Useful family of models for unimodal - symmetric distributions






13. An observational study in which subjects are selected and then their previous conditions or behaviors are determined






14. A numerically valued attribute of a model for a population






15. Multiplying each data value by a constant multiplies both the measures of position and the measures of spread by that constant






16. Shows quantitative data values in a way that sketches the distribution of the data






17. Uses adjacent bars to show the distribution of vales in a quantitative variable; each bar represents the frequency (or relative frequency) of values falling in an interval of values






18. A variable in which the numbers act as numerical values; always has units






19. Any attempt to force a sample to resemble specified attributes of the population






20. In a statistical display - each data value should be represented by the same amount of area






21. Having one mode; this is a useful term for describing the shape of a histogram when it's generally mound-shaped






22. The natural tendency of randomly drawn samples to differ






23. A hump or local high point in the shape of the distribution of a variable; the apparent locations of these can change as the scale of a histogram is changed






24. Distributions with two modes






25. Individuals on whom an experiment is performed






26. A study that asks questions of a sample drawn from some population in the hope of learning something about the entire population






27. Graphs a dot for each case against a single axis






28. Summarized with the mean or the median






29. When omitting a point from the data results in a very different regression model - the point is an ____






30. A numerical summary of how tightly the values are clustered around the 'center'






31. Values of this record the results of each trial with respect to what we were interested in






32. Any data point that stands away from the others; can be extraordinary by having a large residual or by having high leverage






33. The sequence of several components representing events that we are pretending will take place






34. The difference between the lowest and highest values in a data set






35. An equation of the form y-hat = b0 + b1x






36. A sampling design in which the population is divided into several subpopulations - and random samples are then drawn from each stratum






37. The distribution of a variable restricting the who to consider only a smaller group of individuals






38. Bias introduced to a sample when individuals can choose on their own whether to participate in the sample






39. Ideally tells who was measured - what was measured - how the data were collected - where the data were collected - and when and why the study was performed






40. The distribution of either variable alone in a contingency table; the counts or percentages are the totals found in the margins (last row or column) of the table






41. Manipulates factor levels to create treatments - randomly assigns subjects to these treatment levels - and then compares the responses of the subject groups across treatment levels






42. Found by substituting the x-value in the regression equation; they're the values on the fitted line






43. This of sample size n is one in which each set of n elements in the population has an equal chance of selection






44. Gives a value in 'y-units per x-unit'; changes of one unit in x are associated with changes of b1 units in predicted values of y






45. Displays data that change over time






46. The linear equation y-hat = b0 + b1x that satisfies the least squares criterion






47. The entire group of individuals or instances about whom we hope to learn






48. A numerical measure of the direction and strength of a linear association






49. The most basic situation in a simulation in which something happens at random






50. To be valid - an experiment must assign experimental units to treatment groups at random