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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 scatterplot shows an association that is this if there is little scatter around the underlying relationship






2. 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






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






4. Done to eliminate units; values can be compared and combined even if the original variables had different units and magnitudes






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






6. The lower of this is the value with a quarter of the data below it; the upper of this has a quarter of the data above it






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






8. 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






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






10. 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






11. Any individual associated with an experiment who is not aware of how subjects have been allocated to treatment groups






12. Systematically recorded information - whether numbers or labels - together with its context






13. Found by summing all the data values and dividing by the count






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






15. Control - randomize - replicate - block






16. Tells how many standard deviations a value is from the mean; have a mean of zero and a standard deviation of one






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






18. 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






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






20. Consists of the individuals who are conveniently available






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






22. The parts of a distribution that typically trail off on either side; they can be characterized as long or short






23. A variable whose levels are controlled by the experimenter






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






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






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






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






28. 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






29. When averages are taken across different groups - they can appear to contradict the overall averages

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30. The natural tendency of randomly drawn samples to differ






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






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






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






34. 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






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






36. 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






37. 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






38. Doing this is equivalent to changing its units






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






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. Distributions with two modes






42. A sample that consists of the entire population






43. 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






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






45. Extreme values that don't appear to belong with the rest of the data






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






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






48. When an observed difference is too large for us to believe that is is likely to have occurred naturally






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






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