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






2. A variable other than x and y that simultaneously affects both variables - accounting for the correlation between the two






3. Distributions with two modes






4. Values of this record the results of each trial with respect to what we were interested in






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






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






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






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






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






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






11. When omitting a point from the data results in a very different regression model - the point is an ____






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






13. Displays data that change over time






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






15. Distributions with more than two modes






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






17. Anything in a survey design that influences response






18. 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






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






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






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






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






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






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






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






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






27. Useful family of models for unimodal - symmetric distributions






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






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






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

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31. 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






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






33. 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






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






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






36. 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






37. This corresponding to a z-score gives the percentage of values in a standard normal distribution found at that z-score or below






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






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






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






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






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






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






44. The natural tendency of randomly drawn samples to differ






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






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






47. An equation or formula that simplifies and represents reality






48. 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






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






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