1. Chapter Two Observing and Explaining the Economy

2. Figure 2.5: Relative Price of Health Care versus Health-Care Spending Share

3. Correlation vs. Causation  Positive Correlation: While reading a graph from LEFT TO RIGHT, one variable increases as the other increases, moving in the SAME direction (UPWARD HILL)  Negative Correlation: While reading a graph from LEFT TO RIGHT, one variable decreases as the other increases, moving in OPPOSITE directions (DOWNWARD HILL)

4. Figure 2.8: A Model with Two Negatively Related Variables

5. Figure 2.7: A Model with Two Positively Related Variables

6. Causation vs. Correlation, continued  IMPORTANT! – Just because there is a correlation between two variables does not mean that one CAUSED the other.  Correlation: One event is usually observed to occur along with another.  Causation: One event brings about another.  Example: When the thermometer reads 90º, does it CAUSE it to be hot out? NO – they are correlated. However, consider the reverse – when it is hot out does it CAUSE the thermometer to read 90°? YES – that is a CAUSAL relationship.  Back to health-care: We can speak of the CORRELATION, but don’t know about the CAUSATION

7. Reading, Understanding, and Creating Graphs  Cartesian Coordinate Plane: 2 dimensional, x and y axis  Time series graph: Plots a series (several values) of the variable over time.

8. Figure 2A.1: U.S. Federal Debt

9. Figure 2A.2: Stretching the Debt Story in Two Ways – SAME DATA

10. Figure 2A.3: U.S. Federal Debt in Bars

11. Figure 2A.6: Comparing Two Time Series with a Dual Scale

12. Figure 2A.7: Scatter Plot

13. Figure 2A.8: Pie Chart Showing the Shares of the World's GDP

14. Figure 2A.9: Measuring the Slope

15. SLOPE  Slope = rise OR Δy run Δx run Δx  Steeper the curve = Bigger the slope  Almost flat curve = Almost zero slope  Read graphs LEFT TO RIGHT  If slope is constant, then the line is LINEAR and has no bends

16. Figure 2A.10: A Relationship with a Negative Slope

17. Figure 2A.11: Six Types of Relationships