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






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






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






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






5. 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






6. 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






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






8. The ith ___ is the number that falls above i% of the data






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






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






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






12. A display to help assess whether a distribution of data is approximately normal; if it is nearly straight - the data satisfy the nearly normal condition






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






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






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






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






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






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






19. Anything in a survey design that influences response






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






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






22. Individuals on whom an experiment is performed






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






24. 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






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






26. 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






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






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






29. A study that asks questions of a sample drawn from some population in the hope of learning something about the entire population






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






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






32. The ____ we care about most is straight






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






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






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






36. An individual about whom or which we have data






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






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






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






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






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






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






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






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






46. A variable whose values are compared across different treatments






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






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






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






50. A numerical summary of how tightly the values are clustered around the 'center'







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