AP Statistics Flashcards: Introducing Statistics: Do Those Points Align?
Written by AP Content Team, Verified for 2026 AP Exams, Last updated: May 2026
Review key ideas with interactive flashcards. This set includes 10 cards to help you master important concepts.
Why is it important to identify the type of variation (random vs. non-random) in a scatter plot?
Distinguishing between random and non-random variation is crucial for determining if a chosen theoretical line is an appropriate model for the data.
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Why is it important to identify the type of variation (random vs. non-random) in a scatter plot?
Distinguishing between random and non-random variation is crucial for determining if a chosen theoretical line is an appropriate model for the data.
Non-Random Variation (in a scatter plot)
Variation where points are scattered around a theoretical line in a clear, systematic pattern, such as a curve or a fan shape.
What are the two main classifications for variation of points relative to a theoretical line?
The variation in the positions of points relative to a theoretical line can be classified as either random or non-random.
Random Variation (in a scatter plot)
Variation where points are scattered around a theoretical line without any discernible or systematic pattern.
What is the initial step suggested by observing variation in a scatter plot?
The observation of variation in a scatter plot suggests the need to identify and formulate questions about the relationship between the variables.
What is the relationship between variation in a scatter plot and statistical inquiry?
The presence and nature of variation in a scatter plot is the starting point for statistical inquiry, suggesting the specific questions that need to be investigated.
If points on a scatter plot are dispersed unpredictably both above and below a line, what question does this suggest about the model?
This suggests the presence of random variation, which prompts the question of how to measure the strength of the linear association.
A scatter plot of data is created, and the points appear to form a distinct curve. What type of variation is this relative to a straight theoretical line?
This is an example of non-random variation, as the points' positions follow a systematic pattern that is not captured by a straight line.
What fundamental question must be asked about the variation of points around a potential line of fit?
One must ask whether the variation is random, suggesting the line is a reasonable model, or non-random, suggesting a different model is needed.
A plot shows that as the x-variable increases, the points spread out, becoming more varied. What question does this non-random variation suggest?
This suggests a question about whether the variability of the response variable is constant or if it changes as the explanatory variable changes.