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






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






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






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






5. Individuals on whom an experiment is performed






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






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






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






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






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






11. 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






12. Places in order the effects that many re-expressions have on the data






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






14. Sampling schemes that combine several sampling methods






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






16. 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






17. Displays data that change over time






18. When either those who could influence or evaluate the results is blinded






19. Numerically valued attribute of a model






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






21. 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






22. A distribution that's roughly flat






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






24. 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






25. 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






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






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






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






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






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






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






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






33. 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






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






35. 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






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






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






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






40. Distributions with two modes






41. 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






42. Found by substituting the x-value in the regression equation; they're the values on the fitted line






43. The difference between the first and third quartiles






44. A treatment known to have no effect - administered so that all groups experience the same conditions






45. Summarized with the mean or the median






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






47. In a retrospective or prospective study Subjects who are similar in ways not under study may be ____ and then compared with each other on the variables of interest






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






49. The difference between the lowest and highest values in a data set






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