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MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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question d but of 48 what is the answer for with 4.
![### Transcription and Explanation of Pendulum Experiment
#### Experiment Overview
A student experimenting with a pendulum recorded the number of full swings the pendulum made in 20 seconds for various lengths of string. The data collected are presented in a table below:
| Length (in.) | 6.5 | 9 | 11.5 | 14.5 | 18 | 21 | 24 | 27 | 30 | 37 | 43 |
|--------------|-----|---|------|------|----|----|----|----|----|----|----|
| Number of swings | 22 | 20 | 17 | 16 | 14 | 13 | 13 | 12 | 11 | 10 | 9 |
#### Analysis
**(a) Explanation of Linear Model Suitability**
- **Scatterplot Analysis**: A linear model is not appropriate because the scatterplot of Length vs. Number of Swings is not linear, even though the correlation coefficient \( r = -0.94 \) and coefficient of determination \( r^2 = 0.89 \) are relatively strong. The residual plot shows a clear pattern, indicating non-linearity.
**(b) Data Re-expression**
- To straighten the scatterplot, the data were re-expressed as \(\log x\) vs. \(\log y\) and \( \frac{1}{x} \) vs. \( y \).
- **\(\log x\) vs. \(\log y\)**: The scatterplot is made more linear with an improved \( r^2 = 0.99 \) and \( r = -0.995 \). Residuals show no clear pattern.
- **\( \frac{1}{x} \) vs. \( y \)**: Shows a reasonable improvement with \( r^2 = 0.96 \) and \( r = 0.982 \). The pattern in residuals is less clear, reducing outliers.
**(c) Appropriate Model Creation**
- The appropriate model derived is:
\[
\log(\text{Number of Swings}) = -0.45(\log(\text{Length})) + 1.721
\]
**(d) Estimation for a 48-inch Pendulum**
- The estimation for the number of swings a pendulum with a 48](https://content.bartleby.com/qna-images/question/ab37c32c-9a21-47c0-bc8a-d6c0b192dc22/ebe76570-37a2-490a-b338-4aff06da4e3f/78rg4r_thumbnail.png)
Transcribed Image Text:### Transcription and Explanation of Pendulum Experiment
#### Experiment Overview
A student experimenting with a pendulum recorded the number of full swings the pendulum made in 20 seconds for various lengths of string. The data collected are presented in a table below:
| Length (in.) | 6.5 | 9 | 11.5 | 14.5 | 18 | 21 | 24 | 27 | 30 | 37 | 43 |
|--------------|-----|---|------|------|----|----|----|----|----|----|----|
| Number of swings | 22 | 20 | 17 | 16 | 14 | 13 | 13 | 12 | 11 | 10 | 9 |
#### Analysis
**(a) Explanation of Linear Model Suitability**
- **Scatterplot Analysis**: A linear model is not appropriate because the scatterplot of Length vs. Number of Swings is not linear, even though the correlation coefficient \( r = -0.94 \) and coefficient of determination \( r^2 = 0.89 \) are relatively strong. The residual plot shows a clear pattern, indicating non-linearity.
**(b) Data Re-expression**
- To straighten the scatterplot, the data were re-expressed as \(\log x\) vs. \(\log y\) and \( \frac{1}{x} \) vs. \( y \).
- **\(\log x\) vs. \(\log y\)**: The scatterplot is made more linear with an improved \( r^2 = 0.99 \) and \( r = -0.995 \). Residuals show no clear pattern.
- **\( \frac{1}{x} \) vs. \( y \)**: Shows a reasonable improvement with \( r^2 = 0.96 \) and \( r = 0.982 \). The pattern in residuals is less clear, reducing outliers.
**(c) Appropriate Model Creation**
- The appropriate model derived is:
\[
\log(\text{Number of Swings}) = -0.45(\log(\text{Length})) + 1.721
\]
**(d) Estimation for a 48-inch Pendulum**
- The estimation for the number of swings a pendulum with a 48
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