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






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






3. 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






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






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






6. Individuals on whom an experiment is performed






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






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






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






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






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






12. A numerical measure of the direction and strength of a linear association






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






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






15. 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






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






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






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






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






20. A variable whose levels are controlled by the experimenter






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






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






23. 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






24. A variable that names categories (whether with words or numerals)






25. 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






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






27. Doing this is equivalent to changing its units






28. A sample is this if the statistics computed from it accurately reflect the corresponding population parameters






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






30. Displays data that change over time






31. Tells how many standard deviations a value is from the mean; have a mean of zero and a standard deviation of one






32. 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






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






34. Control - randomize - replicate - block






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






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






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






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






39. A point that does not fit the overall pattern seen in the scatterplot






40. The square root of the variance






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






42. 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






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






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






46. Useful family of models for unimodal - symmetric distributions






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






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






49. Gives a value in 'y-units per x-unit'; changes of one unit in x are associated with changes of b1 units in predicted values of y






50. 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