Lesson 1: 4.1 Scatterplots and Correlation

• How do I distinguish between explanatory and response variables for quantitative data?
• How do I make a scatterplot to display the relationship between two quantitative variables?
• How do I describe the direction, form, and strength of a relationship displayed in a scatterplot and identify unusual features?
• How do I interpret the correlation?
• What are the basic properties of correlation, including how the correlation is influenced by unusual points?
• How do I distinguish correlation from causation?

- response variable
- explanatory variable
- scatterplot
- positive association/negative association/no association
- correlation

HSS.ID.B.6 - Represent data on two quantitative variables on a scatter plot, and describe how the variables are related.  
This standard encompasses:
Distinguishing between explanatory and response variables
Creating scatterplots
Describing the direction, form, and strength of relationships
Identifying unusual features in scatterplots

HSS.ID.C.8 - Compute (using technology) and interpret the correlation coefficient of a linear relationship.
This standard covers:
Understanding the correlation coefficient
Interpreting the correlation
Recognizing how unusual points can influence correlation

HSS.ID.C.9 - Distinguish between correlation and causation.

These skills are essential for:
- Data Analysis: Understanding relationships between variables helps us make informed decisions and draw conclusions from data.
- Predictive Modeling: We can use these skills to build models that predict future values of one variable based on another.
- Hypothesis Testing: We can test hypotheses about the relationship between variables using statistical tests.

By mastering these concepts, you can gain valuable insights from data and make data-driven decisions.

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