The scatterplot looks reasonably linear, so linear regression is appropriate. There is an issue of higher spread in the FEV values for higher ages. This could indicate that the variance is not equal for all x-values. We will address this issue later.
The interpretation of the slope ($_1=0.222) is that the mean forced expiratory volume is estimated to increase by 0.222 liters for each one year increase in age.
The interpration of the y-intercept (\(\beta_0=0.4332\)) is that the mean forced expiratory volume for someone who is 0 years old is estimated to be 0.432 liters. This does not make practical sense, since someone who is 0 years old does not have lungs. Even if it did make sense, we did not have any observations with ages near 0, so we should not interpret the intercept.
57.22% of the variation in forced expiratory volume is explained by age.
A correlation of \(r=0.7565\) indicates that the linear relationship between age and FEV is positive and moderately strong.