getting started with tensorflow | tensorflow : I am pretty new to tensorflow,and i am currently learning it through given website https://www.tensorflow.org/get_started/get_started

it is given that, "We've created a model, but we don't know how good it is yet. To evaluate the model on training data, we need a y placeholder to provide the desired values, and we need to write a loss function.

A loss function measures how far apart the current model is from the provided data. We'll use a standard loss model for linear regression, which sums the squares of the deltas between the current model and the provided data. linear_model - y creates a vector where each element is the corresponding example's error delta. We call tf.square to square that error. Then, we sum all the squared errors to create a single scalar that abstracts the error of all examples using tf.reduce_sum:" 

Image of the above quote :https://i.stack.imgur.com/ztdpB.png

q1."we dont know how good it is yet.", i did'nt understand this quote as the simple model created is a simple slope equation and on what it should train for?, as the model is a simple slope. Is it require an perfect slope or what?
why am i training that model and for what?

q2.what is a loss function? Is loss function is used to determine the accuracy of the model? Why is it required?

q3. I did'nt understand " 'sums the squares of the deltas' between the current model and the provided data."

q4.I did'nt understood this part of code,"`squared_deltas = tf.square(linear_model - y)`

this is the code:

`y = tf.placeholder(tf.float32)
squared_deltas = tf.square(linear_model - y)
loss = tf.reduce_sum(squared_deltas)
print(sess.run(loss, {x:[1,2,3,4], y:[0,-1,-2,-3]}))`   

this may be simple questions, but i am a beginner to tensorflow and having a hard time understanding it. Could any one please help me out, thanks :)