Suppose a researcher collects data for the following pair of variables. The researcher wants to make a scatterplot. Identify the response and explanatory variables. What would the researcher expect to see in the scatterplot? Discuss the direction, curvature, and variation. Measuring the lung capacity versus marathon time for a runner. The response variable is the marathon time and the explanatory variable is the lung capacity. The scatterplot should be expected to have a negative direction and be linear with small variation.
Suppose a researcher collects data for the following pair of variables. The researcher wants to make a scatterplot. Identify the response and explanatory variables. What would the researcher expect to see in the scatterplot? Discuss the direction, curvature, and variation. Measuring the lung capacity versus marathon time for a runner. The response variable is the marathon time and the explanatory variable is the lung capacity. The scatterplot should be expected to have a negative direction and be linear with small variation.
MATLAB: An Introduction with Applications
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ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
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Transcribed Image Text:**Title: Analyzing the Relationship Between Lung Capacity and Marathon Time**
**Introduction:**
Suppose a researcher collects data for the following pair of variables. The researcher wants to create a scatterplot. What would the researcher expect to see in the scatterplot? We will examine the direction, curvature, and variation of the data.
**Variables:**
- **Response Variable:** Marathon time
- **Explanatory Variable:** Lung capacity
**Expected Scatterplot Characteristics:**
1. **Direction:** Negative
- A negative direction indicates that as lung capacity increases, marathon time is expected to decrease.
2. **Curvature:** Linear
- A linear relationship suggests that the change in marathon time is consistent with changes in lung capacity.
3. **Variation:** Small
- Small variation implies that marathon times are closely associated with lung capacity, with minimal scatter or deviation from the trend line.
**Conclusion:**
In summary, a scatterplot depicting lung capacity versus marathon time is anticipated to show a negative linear relationship with small variation. This observation can be useful for understanding how physiological factors influence athletic performance.
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