I'm completely blind and come from a programming background.

What I'm trying to do is to learn machine learning, and to do this, I first need to learn about linear regression. All the explanations on the Internet I am finding about this subject plot the data first. I'm looking for a practical explanation of linear regression that is not dependent on graphs and plots.

Here is my understanding of the aim of simple linear regression:

Simple linear regression is trying to find the formula that once you give X to it, would provide you with the closest estimation of Y.

So, as I understand it, what needs to be done is to compare the predictor (for example the area of a house in square feet) with the independent variable (the price). In my example, you probably can create a non-visual way of getting the best formula to calculate the price of a house from its area. For example, maybe you would get the area and price of 1000 houses in a neighborhood, and divide the price to the area? The result (at least in Iran which is where I live) would have a very negligible variance. So you'd probably get something like this:

Price = 2333 Rials * Area of the house 

So, why would you need a scatter plot and linear algebra for this?

First, am I right in my assumptions? If not, I'd love to be corrected. Whether or not I am, though, is there a way to come up with the formula without playing around with linear algebra?

I would really appreciate it if I could get an example with the explanation, so that I can do it along with the text to test my understanding.

I'm completely blind and come from a programming background.

What I'm trying to do is to learn machine learning, and to do this, I first need to learn about linear regression. All the explanations on the Internet I am finding about this subject plot the data first. I'm looking for a practical explanation of linear regression that is not dependent on graphs and plots.

Here is my understanding of the aim of simple linear regression:

Simple linear regression is trying to find the formula that once you give X to it, would provide you with the closest estimation of Y.

So, as I understand it, what needs to be done is to compare the predictor (for example the area of a house in square feet) with the independent variable (the price). In my example, you probably can create a non-visual way of getting the best formula to calculate the price of a house from its area. For example, maybe you would get the area and price of 1000 houses in a neighborhood, and divide the price to the area? The result (at least in Iran which is where I live) would have a very negligible variance. So you'd probably get something like this:

Price = 2333 Rials * Area of the house 

Of course, you would then need to go through all the 1000 houses in your data set, put the area in the formula above, compare the estimate with the real price, square the results (I guess to prevent variances from canceling each other out) and then get a number, then keep playing around with the 2333 to decrease the errors.

Of course, this is the brute force option where it will probably take ages to compute the errors and arrive at the best option, but you see what I'm saying? I didn't say anything about a graph, or a line, or points on a plot, or the best way of fitting a line to your existing data.

So, why would you need a scatter plot and linear algebra for this? Isn't there a non-visual way?

First, am I right in my assumptions? If not, I'd love to be corrected. Whether or not I am, though, is there a way to come up with the formula without playing around with linear algebra?

I would really appreciate it if I could get an example with the explanation, so that I can do it along with the text to test my understanding.

I'm completely blind and come from a programming background.

What I'm trying to do is to learn machine learning, and to do this, I first need to learn about linear regression. All the explanations on the Internet I am finding about this subject plot the data first. I'm looking for a practical explanation of linear regression that is not dependent on graphs and plots.

I would really appreciate it if I could get an example with the explanation, so that I can do it along with the text to test my understanding.

I'm completely blind and come from a programming background.

What I'm trying to do is to learn machine learning, and to do this, I first need to learn about linear regression. All the explanations on the Internet I am finding about this subject plot the data first. I'm looking for a practical explanation of linear regression that is not dependent on graphs and plots.

Here is my understanding of the aim of simple linear regression:

Simple linear regression is trying to find the formula that once you give X to it, would provide you with the closest estimation of Y.

So, as I understand it, what needs to be done is to compare the predictor (for example the area of a house in square feet) with the independent variable (the price). In my example, you probably can create a non-visual way of getting the best formula to calculate the price of a house from its area. For example, maybe you would get the area and price of 1000 houses in a neighborhood, and divide the price to the area? The result (at least in Iran which is where I live) would have a very negligible variance. So you'd probably get something like this:

Price = 2333 Rials * Area of the house 

So, why would you need a scatter plot and linear algebra for this?

First, am I right in my assumptions? If not, I'd love to be corrected. Whether or not I am, though, is there a way to come up with the formula without playing around with linear algebra?

I would really appreciate it if I could get an example with the explanation, so that I can do it along with the text to test my understanding.