For Q3, we want to know which model type best fits the data. The R-squared value will essentially tell us how close the data points are fitted to the regression line (closer to 0 means poor fit, closer to 1 means good fit), so all we need to do is compare the R-squared values between the different types of models and pick the highest one.

The R^2 represents how a model describe data. When setting the model as polynomial with 2 degree, the R^2 is around 0.156, which is the largest R^2 compared with other models.

Can someone explain why the answer for Q3 is Polunomial with degree two?

Thanks,

Hi

Different model type of trendlines have different shapes. I cannot paste picture here but you may google it.

Thanks,

Iris

For Q3, we want to know which model type best fits the data. The R-squared value will essentially tell us how close the data points are fitted to the regression line (closer to 0 means poor fit, closer to 1 means good fit), so all we need to do is compare the R-squared values between the different types of models and pick the highest one.

The R^2 represents how a model describe data.

When setting the model as polynomial with 2 degree, the R^2 is around 0.156, which is the largest R^2 compared with other models.