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Answer with explanation:</h2>
When there is a linear relationship is observed between the variables, we use linear regression predict the relationship between them.
Also, we predict the values for dependent variable by modelling a linear model that best fits the data by drawing a line Y=a+bX, where X is the explanatory variable and Y is the dependent variable.
In other words: The line of best fit is a line through a scatter plot of data points that best describes the relationship between them.
That's why the regression line referred to as the line of best fit.
Using slope-intercept form, y = mx + b where m = slope and b = y-intercept:
We know our slope is -6. This can be interpreted as -6/1, which rise-over-run-wise, means that when y changes by 6, x changes inversely by 1.
To find that y-intercept, though, we need to find the value of y when x = 0.
Use our point (-9, -3) to find this...
We want to add 9 to x so that it becomes 0.
According to our slope, this means subtracting 54 from y.
Our y-intercept is at (0, -57), with -57 being the value of b we put in our equation.

You could also just use point-slope form:
y - y¹ = m(x - x¹)
y - (-3) = -6(x - (-9))
y + 3 = -6(x + 9)
And convert to slope-intercept if you want:
y + 3 = -6x - 54
y = -6x - 57
Answer:
i don't really understand what you are asking me
Step-by-step explanation:
Answer:

Step-by-step explanation:

Cancel 4c on both the sides of the equation.

Bring the 2 in the denominator of 11/2 to the left hand side of the equation.

Bring 4 to the right hand side if the equation.


Answer:
*sum
Step-by-step explanation:
i am not sure. But I just wanted to correct it for someone else