10. You are given the following data and scattaerplot: y 2 1 16 8. 14 6 7 12 10 10 10 15 8 a) Perform a linear regression. Give the equation as well as the value for r. 6. 4 2 2 6 8 10 12 b) What proportion of the total variation of y is explained by the linear model? c) What is the value of the linear correlation coefficient?|
10. You are given the following data and scattaerplot: y 2 1 16 8. 14 6 7 12 10 10 10 15 8 a) Perform a linear regression. Give the equation as well as the value for r. 6. 4 2 2 6 8 10 12 b) What proportion of the total variation of y is explained by the linear model? c) What is the value of the linear correlation coefficient?|
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Transcribed Image Text:### Transcription and Explanation
**10. You are given the following data and scatterplot:**
#### Data Table:
- **x** | **y**
- 0 | 2
- 1 | 6
- 5 | 8
- 6 | 7
- 8 | 10
- 10 | 15
#### Scatterplot:
A graph is provided with the data points plotted, showing the distribution of the values of x and y. The horizontal axis represents the value of x ranging from 0 to 12, and the vertical axis represents y ranging from 0 to 16.
---
#### Questions:
**a) Perform a linear regression. Give the equation as well as the value for \( r^2 \).**
**b) What proportion of the total variation of y is explained by the linear model?**
**c) What is the value of the linear correlation coefficient?**
---
### Diagram Explanation:
The scatterplot shows a positive correlation between x and y values. Points are distributed in a way that suggests a linear relationship, with a general upward trend as x increases.
The tasks involve finding the linear regression equation for the set of data points, which can be used to predict y from x. Additionally, calculating \( r^2 \) will show how well the regression line fits the data, indicating the proportion of variance in y explained by this linear model. The correlation coefficient will provide insight into the strength and direction of the linear relationship between x and y.
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