The plot above shows the data points along with three different regression fits: linear (red line), quadratic (green line), and cubic (purple line).

Using the quadratic equation, the predicted height for someone with a 45 cm femur is approximately 169.47 cm.

Would you like more details on how these regressions were calculated, or do you have any other questions? Here are some related questions to explore further:

1. How do linear, quadratic, and cubic regressions differ in terms of their application?
2. Why might a quadratic model be a better fit than a linear model in this scenario?
3. What are the limitations of using higher-order polynomials for predictions?
4. How can we assess the goodness of fit for these models?
5. Can we apply these models to predict heights for femur lengths outside the provided data range?

Tip: When choosing a regression model, it's important to consider not only the fit but also the complexity of the model. Simpler models (like linear regression) are easier to interpret and may generalize better to new data.