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Analyzing Relationships Between Quantitative Data: A Case Study on Length and Weight

This section explores the relationship between two sets of quantitative data, using the example of length and weight in channel iron. It explains the process of calculating the correlation coefficient step-by-step, revealing a strong correlation with a remarkable value of r = 0.998. Additionally, it compares this with the temperature/elevation analysis, which yields a significant negative correlation of r = -0.951, indicating an inverse relationship. For ease of calculation, a TI-84 calculator is recommended, and a helpful video link is provided.

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Analyzing Relationships Between Quantitative Data: A Case Study on Length and Weight

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Presentation Transcript

  1. Section 4.1 How Can We Describe the Relationship between two sets of Quantitative Data?

  2. Consider the Relationship Between Length and Weight in some Lengths of Channel Iron:

  3. Scatter Plot

  4. Correlation Coefficient • Here is how to do it by hand: • Compute • Determine for each observation • Compute for each observation • Determine • Divide the sum by n-1

  5. Channel Iron Correlation: • = 35.8 & Sx = 15.1888 • = 319.6 & Sy= 151.4754 • Correlation Coefficient is r = .998 … strong correlation!!! r = = .998

  6. Temp/Elevation Correlation: • Calculate the Correlation Coefficient • r = -.951 • What does the negative value reveal about the data?

  7. Temp/Elevation Correlation: • Let’s get the TI – 84 to do all this tedious work for us • Web link to a good graphing calculator regression: • http://www.youtube.com/watch?v=nw6GOUtC2jY

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