Which ONE of the following is NOT an assumption of the...

Which ONE of the following is NOT an assumption of the linear regression model? - The relationship between x and the mean of Y at X = x is linear. - The random errors are Normally distributed. - The random errors are all independent. - The values of x are Normally distributed. - The random errors all have the same standard deviation regardless of the value of x.

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00:01 Hey everyone, welcome to numerate.

00:04 So we are given problem here to see what assumption on the linear regression distribution is not the one that follows, right? so we are given choices a to e.

00:21 Let's go through each one.

00:25 Let's go through a first.

00:31 Okay, a.

00:34 So the relationship between x and the mean of y is linear.

00:40 Between the y, mean y and x, right? so let's see if that's true.

00:51 So this actually just means that the, um, regression distribution, distribution is linear and is a closely correlated, right? okay.

01:08 And this seems true for a regression model.

01:12 So let's go to b.

01:13 The random errors are normally distributed.

01:16 So since we, have a linear regression model, the errors should be normally distributed.

01:32 Since we follow a regression model, right, since everything is linear, therefore it should be normally distributed.

01:43 Okay, so see, the random errors are all independent.

01:48 So let's see the random errors, errors are independent.

01:57 So in most cases, the random errors that we calculate will be independent from each other in a regression model.

02:07 Right...

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