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






2. Data points whose x-values are far from the mean of x are said to exert ____ on a linear model; with high enough ____ - residuals can appear to be deceptively small






3. A variable whose levels are controlled by the experimenter






4. Control - randomize - replicate - block






5. An observational study in which subjects are followed to observe future outcomes






6. The square root of the variance






7. When the levels of one factor are associated with the levels of another factor so their effects cannot be separated






8. Any systematic failure of a sampling method to represent its population; common errors are voluntary response - undercoverage - nonresponse ____ - and response ____






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






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






11. A variable that names categories (whether with words or numerals)






12. Sampling schemes that combine several sampling methods






13. A value that attempts the impossible by summarizing the entire distribution with a single number - a 'typical' value






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






15. This - b0 - gives a starting value in y-units; it's the y-hat-value when x is 0






16. 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






17. A sampling design in which entire groups are chosen at random






18. The difference between the first and third quartiles






19. An event is this if we know what outcomes could happen - but not which particular values will happen






20. Displays data that change over time






21. A variable whose values are compared across different treatments






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






23. A sample drawn by selecting individuals systematically from a sampling frame






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






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






26. The process - intervention - or other controlled circumstance applied to randomly assigned experimental units






27. A distribution that's roughly flat






28. Bias introduced to a sample when a large fraction of those sampled fails to respond






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






30. The experimental units assigned to a baseline treatment level - typically either the default treatment - which is well understood - or a null - placebo treatment






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






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






33. Consists of the individuals who are conveniently available






34. The best defense against bias - in which each individual is given a fair - random chance of selection






35. The number of individuals in a sample






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






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






38. This criterion specifies the unique line that minimizes the variance of the residuals or - equivalently - the sum of the squared residuals






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






40. Shows a bar representing the count of each category in a categorical variable






41. The sum of squared deviations from the mean - divided by the count minus one






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






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






44. When either those who could influence or evaluate the results is blinded






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






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






47. The specific values that the experimenter chooses for a factor






48. Each predicted y-hat tends to be fewer standard deviations from its mean than its corresponding x was from its mean






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






50. Holds information about the same characteristic for many cases