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






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






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






4. 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






5. To be valid - an experiment must assign experimental units to treatment groups at random






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






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






8. The difference between the first and third quartiles






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






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






11. 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






12. Displays data that change over time






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






14. 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






15. The number of individuals in a sample






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






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






18. Individuals on whom an experiment is performed






19. 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






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






21. The square root of the variance






22. The ____ we care about most is straight






23. 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






24. 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






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






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






27. In a statistical display - each data value should be represented by the same amount of area






28. 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






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






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






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






32. 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






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






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






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






36. An equation or formula that simplifies and represents reality






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






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






39. Holds information about the same characteristic for many cases






40. Distributions with two modes






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






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






43. 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






44. 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






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






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






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






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






49. A variable whose values are compared across different treatments






50. 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