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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 most basic situation in a simulation in which something happens at random






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






3. 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






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






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






6. Distributions with two modes






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






8. 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






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






10. 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






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






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






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






14. When groups of experimental units are similar - it is a good idea to gather them together into these






15. The square root of the variance






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






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






18. Consists of the individuals who are conveniently available






19. A distribution is this if the two halves on either side of the center look approximately like mirror images of each other






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






21. 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






22. Numerically valued attribute of a model






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






24. The number of individuals in a sample






25. The ____ we care about most is straight






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






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






28. The linear equation y-hat = b0 + b1x that satisfies the least squares criterion






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






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






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






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






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






34. 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






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






36. 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






37. This corresponding to a z-score gives the percentage of values in a standard normal distribution found at that z-score or below






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






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






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






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






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






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






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






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






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






47. 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






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






49. Useful family of models for unimodal - symmetric distributions






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