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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 sample that consists of the entire population






2. 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






3. 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






4. The difference between the first and third quartiles






5. Distributions with more than two modes






6. A positive ____ or association means that - in general - as one variable increases - so does the other; when increases in one variable generally correspond to decreases in the other - the association is negative






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






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






9. 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






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






11. 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






12. 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






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






14. Distributions with two modes






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






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






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






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






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






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






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






22. Displays data that change over time






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






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






25. A normal model with a mean of 0 and a standard deviation of 1






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






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






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






29. 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






30. The square root of the variance






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






32. Sampling schemes that combine several sampling methods






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






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






35. When both those who could influence and evaluate the results are blinded






36. An individual about whom or which we have data






37. Useful family of models for unimodal - symmetric distributions






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






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






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






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






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






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






44. 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






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






46. 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






47. Consists of the individuals who are conveniently available






48. To describe this aspect of a distribution - look for single vs. multiple modes - and symmetry vs. skewness






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






50. The tendency of many human subjects (often 20% or more of experiment subjects) to show a response even when administered a placebo