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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. 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






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






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






4. A list of individuals from whom the sample is drawn






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






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






7. 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






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






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






10. 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






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






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






13. 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






14. Useful family of models for unimodal - symmetric distributions






15. Distributions with two modes






16. An observational study in which subjects are selected and then their previous conditions or behaviors are determined






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






18. A sample that consists of the entire population






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






20. 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






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






22. A distribution is this if it's not symmetric and one tail stretches out farther than the other






23. 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






24. Graphs a dot for each case against a single axis






25. A variable whose levels are controlled by the experimenter






26. Shows how a 'whole' divides into categories by showing a wedge of a circle whose area corresponds to the proportion in each category






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






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






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






30. Distributions with more than two modes






31. 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






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






33. Anything in a survey design that influences response






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






35. Design Randomization occurring within blocks






36. The difference between the first and third quartiles






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






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






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






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






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






42. The lower of this is the value with a quarter of the data below it; the upper of this has a quarter of the data above it






43. 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






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






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






46. Individuals on whom an experiment is performed






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

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48. Doing this is equivalent to changing its units






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






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