The following standards will be assessed on the LIN quiz:

ALG-LIN

You should be able to:

• Explain the process of the linear regression algorithm
• Define the following terms: objective function, cost function, gradient descent, learning rate
• Interpret gradients and give suggestions for possible model improvement

FLOW-LIN

You should be able to:

• Analyze and critique a given five-step workflow using linear models

Study Tips

Review the lecture slides, workbooks, homework assignments, and the associated lab.
Quiz questions are similar (though not identical) to the types of questions covered in these materials. You should be able to use appropriate terminology and apply the concepts covered in class to a variety of new scenarios.

The primary goal of each quiz is to give you an opportunity to apply concepts with clear and well-explained reasoning.
Quizzes are also a valuable opportunity to receive feedback on your reasoning skills.

Formulas Given

\(\text{MAE}: \frac{1}{n}\Sigma |y_{obs} - y_{pred}|\)
\(\text{MSE}: \frac{1}{n}\Sigma (y_{obs} - y_{pred})^2\)
\(\text{RMSE}: \sqrt{\text{MSE}}\)
\(y_{pred}=\beta_1 x_1+\beta_0\)

\(\nabla C(x,y) = (\frac{\delta C}{\delta y}(x,y), \frac{\delta C}{\delta x}(x,y)\)
\((\beta_0*, \beta_1* ) = (\beta_0, \beta_1) + l \times(-\nabla C(\beta_0, \beta_1))\)