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






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






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






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

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






6. 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






7. Found by summing all the data values and dividing by the count






8. 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






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






10. 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






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






12. Consists of the individuals who are conveniently available






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






14. An individual about whom or which we have data






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






16. Summarized with the mean or the median






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






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






19. Design Randomization occurring within blocks






20. Control - randomize - replicate - block






21. 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






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






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






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






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






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






27. 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






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






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






30. Value calculated from data to summarize aspects of the data






31. The sequence of several components representing events that we are pretending will take place






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






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






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






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






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






37. These are hard to generate - but several websites offer an unlimited supply of equally likely random values






38. 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






39. 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






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






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






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






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






44. The ____ we care about most is straight






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






46. Displays data that change over time






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






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






49. A sample that consists of the entire population






50. 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