Regression analysis

I have seen your lecture on regression analysis but I could not understand it completely.

What I understand is that regression analysis is used to identify a straight line that shows a linear relationship between two variables.

Is it true that these two variables are total cost (y) and the number of units (x)?

It shows the relationship between two variables that if one variable (number of units (x)) is increasing then the other variable (total costs (y)) will also be increasing. It simply means that with more units produced there will be more total costs of production.

To show this relationship we need to calculate the fixed cost and variable cost using regression analysis formula

Y = a + bx

We could be asked regression analysis calculations only in sections A and B in paper PM?

Thank you so much. 🙂
Please say about this too.

Correlation Coefficient:
It measures how linear the relationship is between two variables such as whether it is perfectly positive linear correlation or not using this formula.

r = (n(Exy) – Ex Ey / squareroot n(Ex^2 – (Ex)^2)) x (nEy^2 – (Ey)^2)

+ 1 = The points are exactly on a straight-line going upwards
1 = The points are closely on a straight-line going upwards
– 1 = The points are exactly on a straight-line going downwards
0 = No correlation at all (straight-line is not possible to draw)

The correlation coefficient is used only to see whether the straight-line which is passing through the points are perfectly or not perfectly positive or negative.

Is it correct?

Is it also correct that linear relationship refers to the straight-line which passes through points (or variable points) but the linear relationship refers to only two variables only. I don’t understand why is it important though?