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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 specific values that the experimenter chooses for a factor






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






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






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






5. The distribution of either variable alone in a contingency table; the counts or percentages are the totals found in the margins (last row or column) of the table






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






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






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






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






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






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






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






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






14. Individuals on whom an experiment is performed






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






16. 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






17. 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






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






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






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






21. A variable whose values are compared across different treatments






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






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






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






25. The number of individuals in a sample






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






27. 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






28. A sample that consists of the entire population






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






30. A variable whose levels are controlled by the experimenter






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






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






33. 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






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






35. The difference between the first and third quartiles






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






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






38. The square root of the variance






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






40. An individual about whom or which we have data






41. Distributions with two modes






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






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






44. Holds information about the same characteristic for many cases






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






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






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






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






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






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