STAT.MATH.7.A
Analyze scatterplots for patterns, linearity, outliers, and influential points.
Statistics · Texas Essential Knowledge and Skills (TEKS) · TEKS 2012
Standard Unwrapping
AI-generated as a starting point — sign in to edit.Vocabulary
scatterplotspatternslinearityoutliersinfluential pointsbivariate quantitative data
Skills
- analyze (scatterplots for patterns) #dok2
- analyze (scatterplots for linearity) #dok2
- identify (outliers in scatterplots) #dok1
- identify (influential points in scatterplots) #dok1
- interpret (the meaning of patterns, outliers, and influential points in context) #dok3
Learning Targets
- I can identify outliers and influential points in a scatterplot. #dok1
- I can analyze scatterplots for patterns and linearity. #dok2
- I can interpret the impact of outliers and influential points on the relationship between two variables. #dok3
Big Ideas
- Patterns, linearity, outliers, and influential points in scatterplots provide valuable insight into the relationship between two quantitative variables.
- Recognizing and interpreting scatterplot features are essential for making sense of data and informing further statistical investigations.
Essential Questions
- How do you determine whether a scatterplot shows a linear relationship between two variables?
- What is the significance of outliers and influential points in a data set?
- How can identifying patterns in a scatterplot help you understand the data?
- Why might influential points dramatically affect the interpretation of the data?
- What steps would you take to analyze a scatterplot for both patterns and anomalies?