https://file.aiquickdraw.com/mathbot/file/1727322934350rts1ctdo.jpg

The image shows a problem involving linear regression based on a dataset of paired \((x, y)\) values.

Here is the dataset:

\[
\begin{array}{|c|c|}
\hline
x & y \\
\hline
2 & 3 \\
4 & 4 \\
7 & 9 \\
\hline
\end{array}
\]

### (a) Line of Best Fit:
You are asked to use linear regression to find the equation of the "Line of Best Fit," which is given as:

\[
y = 1.2x + 0.6
\]
This equation is already rounded to 3 decimal places.

### (b) Correlation Coefficient:
The correlation coefficient \( r \), which measures the strength and direction of the linear relationship between \( x \) and \( y \), is given as:

\[
r = 0.998
\]
This value is also rounded to 3 decimal places, indicating a very strong positive linear relationship between the variables.

Would you like me to explain in detail how these results are calculated or if you have any further questions?

### Five Related Questions:
1. How do you compute the slope and y-intercept of the line of best fit using linear regression formulas?
2. What does the correlation coefficient tell you about the data's relationship?
3. Can you perform linear regression on more than two variables, and how would that work?
4. What does it mean if the correlation coefficient is 0 or negative?
5. How would you predict future values using the line of best fit equation?

### Tip:
In linear regression, the closer the correlation coefficient \( r \) is to 1 or -1, the stronger the relationship between the two variables.

Consider the dataset below:

x | y
2 | 3
4 | 4
7 | 9

(a) Use linear regression to find the 'Line of Best Fit.'
(b) What is the correlation coefficient?

Learn how to perform linear regression to find the Line of Best Fit and calculate the correlation coefficient for the dataset (x, y). The problem provides the regression line y = 1.2x + 0.6 and a correlation coefficient r = 0.998.

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