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






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






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






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






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






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






7. 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






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






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






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

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






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






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






14. Consists of the minimum and maximum - the quartiles Q1 and Q3 - and the median






15. A sampling scheme that biases the sample in a way that gives a part of the population less representation than it has in the population






16. 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






17. Individuals on whom an experiment is performed






18. Summarized with the standard deviation - interquartile range - and range






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






20. Adding a constant to each data value adds the same constant to the mean - the median - and the quartiles - but does not change the standard deviation or IQR






21. Design Randomization occurring within blocks






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






23. Value found by subtracting the mean and dividing by the standard deviation






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






25. A sample is this if the statistics computed from it accurately reflect the corresponding population parameters






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






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






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






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






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






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






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






33. The natural tendency of randomly drawn samples to differ






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






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






36. Numerically valued attribute of a model






37. 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






38. The square root of the variance






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






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






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






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






43. 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






44. 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






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






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






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






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






49. The difference between the first and third quartiles






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