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






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






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






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






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






6. Multiplying each data value by a constant multiplies both the measures of position and the measures of spread by that constant






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






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






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






10. 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






11. 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






12. 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






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






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






15. 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






16. Doing this is equivalent to changing its units






17. 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






18. 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






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






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






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






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






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






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






25. An equation or formula that simplifies and represents reality






26. 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






27. 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






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. A numerically valued attribute of a model for a population






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






31. The square root of the variance






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






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






34. A sample that consists of the entire population






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






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






37. 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






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






39. The difference between the first and third quartiles






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






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






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






43. Holds information about the same characteristic for many cases






44. Sampling schemes that combine several sampling methods






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






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






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






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






49. Distributions with more than two modes






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