estimated simple linear regression equation

So, if you think about it, you might want to pause this and see if you can figure it out. I'm just putting a little stars on the intercept slope here to estimate that they may be different than the values we looked at before when the coding was a one for females and zero.

So, the question I have for you now is suppose we had coded the variable as a one for male children and a zero for female children and we can fit the following regression line. And here, the intercept estimate is the estimated outcome, the mean arm circumference when x1 is equal to zero, when we're looking at the reference group of males. So, females had lower arm circumference on average than males by 0.13 centimeters. Here, we have a binary predictor which is coded as a one for female children and a zero for males, and hence, the slope estimate of negative 0.13 estimated the mean difference in arm circumference between females and males in the direction of female to male. We had originally looked at this with a linear regression model. So, first thing I want to revisit as the relationship between arm circumference and sex of the child. Let's look at some additional examples related to linear regression.

Estimated simple linear regression equation