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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. Variables are said to be this if the conditional distribution of one variable is the same for each category of the other






2. Gives the possible values of the variable and the relative frequency of each value






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






4. All experimental units have an equal chance of receiving any treatment






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






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






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






8. An individual result of a component of a simulation






9. The differences between data values and the corresponding values predicted by the regression model; ____ = observed value - predicted value






10. A point that does not fit the overall pattern seen in the scatterplot






11. Control - randomize - replicate - block






12. Places in order the effects that many re-expressions have on the data






13. Sampling schemes that combine several sampling methods






14. In a retrospective or prospective study Subjects who are similar in ways not under study may be ____ and then compared with each other on the variables of interest






15. 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






16. A study based on data in which no manipulation of factors has been employed






17. Lists the categories in a categorical variable and gives the count or percentage of observations for each category






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






19. When doing this - consider their shape - center - and spread






20. Distributions with two modes






21. These are hard to generate - but several websites offer an unlimited supply of equally likely random values






22. Doing this is equivalent to changing its units






23. Distributions with more than two modes






24. 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






25. We do this by taking the logarithm - the square root - the reciprocal - or some other mathematical operation on all values in the data set






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






27. If data consist of two or more groups that have been thrown together - it is usually best to fit different linear models to each group than to try to fit a single model to all of the data






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






29. 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






30. Although linear models provide an easy way to predict values of y for a given value of x - it is unsafe to predict for values of x far from the ones used to find the linear model equation; predictions should not be trusted






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






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






33. Anything in a survey design that influences response






34. A quantity or amount adopted as a standard of measurement - such as dollars - hours - or grams






35. A variable other than x and y that simultaneously affects both variables - accounting for the correlation between the two






36. Shows how a 'whole' divides into categories by showing a wedge of a circle whose area corresponds to the proportion in each category






37. 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






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






39. A variable that is not explicitly part of a model but affects the way the variables in the model appear to be related






40. 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






41. Individuals on whom an experiment is performed






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






43. A variable whose values are compared across different treatments






44. 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






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






46. Numerically valued attribute of a model






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






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






49. A distribution is this if the two halves on either side of the center look approximately like mirror images of each other






50. When groups of experimental units are similar - it is a good idea to gather them together into these