This document discusses how to describe scatterplots based on four key things: direction, form, scatter, and unusual elements. Direction can be positive, negative, or null depending on how the explanatory and response variables change together. Form can be linear, curved, or none. Scatter indicates the strength of association, from strong to weak. Unusual elements include outliers or changes in scatter.

1. Chapter 2 Relationships Scatterplots – Descriptions

2. Scatterplots Graphical display of two quantitative variables We plot the explanatory (independent) variable on the x-axis and the response (dependent) variable on the y-axis Each dot represents a single observation and it’s two values

3. Describing Scatterplots 4 things that must be talked about: Direction Form Scatter Unusual elements

4. Direction Positive: as values of the explanatory variable increase, values in the response variable tend to increase

5. Direction Negative: as values of the explanatory variable increase, value in the response variable tend to decrease

6. Direction Null: no discernable change in the response variable

7. Form (Shape) Linear: The shape has the appearance of a linear relationship. Does not have to fit it perfectly.

8. Form Curved Some can be transformed to linear graphs. (Coming Soon)

9. Form None No discernable form

10. Strength (Scatter) Strong association: very little scatter

11. Strength Moderate strength:

12. Strength Weak strength: lots of scatter

13. Unusual Features Outliers

14. Unusual Features Look for changes in the scatter. A horn shape:

15. Practice The scatterplot shows a moderately strong, negative association that is curved.

16. The scatterplot shows a weak, positive linear association. The scatter tends to decrease as the scores in Exam 1 increase.

17. The scatterplot shows a moderately strong, positive linear association. There appears to be an outlier around (9, 35).

18. The scatterplot shows no apparent association. There is great scatter and an outlier around (60,8).