00:02
Hello, so i'm going to explain the results of our regression.
00:06
For doing so first i write that here the regression results, here the r squared, and here the e's er.
00:16
So the first question, what is the gender gap? for calculating the difference, you need to consider the equation when the dummy variable assume the value of 1, and then subscribe when the whole regression assume the value of 0.
00:27
So it would be 12 .52 plus 2 .12.
00:31
That is the case when it's a male, minus the regression, 12 .52, when is the case of a female.
00:37
So as you can see, these two values can sell later between each other.
00:41
This value, because it's times zero, it's zero.
00:43
So the only value remaining is this.
00:45
So this will be the wage gap in terms of gender.
00:49
They then ask you to calculate gender gap is significant.
00:52
The weight to do it is you need to take the cita value and take the x minus the mean over the standard error.
01:00
In your case, you know that you want to prove is that this is equal to 0, so it will be x minus 0 over the standard error, that is 0 .36.
01:08
This gives you 6 .13.
01:10
Just to give you general understanding, when it's above 1 .86, it's significant to 95 % level.
01:18
And when it's above 2 .5, it's 99%.
01:25
So as you can see, this value clearly exceeds.
01:28
So you can reject h0 at the whole levels.
01:31
And in your case your no hypothesis or h0 is that the 2 .12 was equal to 0, so you can see that is significant at all the levels of significance...