
MATLAB: An Introduction with Applications
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ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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Transcribed Image Text:**Understanding Regression Analysis with Lemon Imports and Crash Fatality Rates**
**Task Explanation:**
The objective is to find the regression equation, using lemon imports as the predictor (x) variable. The data pairs lemon imports in metric tons and crash fatality rates per 100,000 people. The goal is to predict the crash fatality rate for a year with 475 metric tons of lemon imports, and assess if this prediction is worthwhile.
**Data Presented:**
- Lemon Imports (Metric Tons): 226, 260, 354, 488, 511
- Crash Fatality Rate (Per 100,000 People): 16, 15.7, 15.4, 15.4, 15
**Steps to Obtain the Regression Equation:**
1. **Find the Equation of the Regression Line:**
- Use the formula \(\hat{y} = a + bx\).
- \(a\) represents the y-intercept (round to three decimal places).
- \(b\) is the slope coefficient (round to six decimal places).
2. **Prediction for Given Data:**
- Determine the best predicted crash fatality rate when lemon imports are 475 metric tons (round to one decimal place).
3. **Evaluate Prediction Worth:**
- Options to consider regarding the prediction's validity:
- **A:** All regression line requirements met; prediction is worthwhile.
- **B:** Lack of logical relationship suggests prediction is nonsensical.
- **C:** Presence of an outlier makes prediction inappropriate.
- **D:** Small sample size renders prediction inappropriate.
**Conclusion:**
After inserting the required calculations, select the most reasonable answer regarding the prediction's worthiness.
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