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Exploring the Association Between TV Watching and Obesity: A Correlation Analysis

Analyzing the relationship between average TV hours and obesity rates in 18 countries using scatter plots and correlation values to determine the strength and direction of the association.

molly-sharpe
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Exploring the Association Between TV Watching and Obesity: A Correlation Analysis

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  1. Section 4.1 Exploring Associations between Two Quantitative Variables?

  2. Example: • Is there, on a national scale, an association between TV watching and obesity? • What do you think? • What does the data Show?

  3. Data: The average hours of TV watched by adults in 18 industrialized countries and the Obesity rate of adults in those countries. Does there seem to be a associated? Lets look at a bar graph and see if that helps.

  4. Data:

  5. New Tool: Scatter Plot: • To build a scatter plot treat your explanatory variable as x, and your response variable as y, and plot your data on an (x , y) plane.

  6. New Tool: Scatter Plot: • We look at three things on a scatter Plot: • Is there a linear association? • What is the direction? • How strong is the association?

  7. Correlation. • Correlation is a numerical value that summarizes the direction and strength of the association between two quantitative variables. • Properties: • Denoted r. • Positive r indicated a positive association • Negative r indicated a negative association • Values fall within the interval [-1, 1] • The closer to r = zero the weaker the association.

  8. Correlation Would you expect a positive association, a negative association or no association between the age of the car and the mileage on the odometer? • Positive association • Negative association • No association

  9. New Tool: Scatter Plot: • What would we expect as the r value for the scatter plot below?

  10. Questions

  11. Calculating Correlation.

  12. Remember the TV thing: r = 0.5378

  13. Remember the TV thing: r = 0.0884

  14. Questions

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