$1.$ Write a paragraph that summarizes the main concepts covered in this lesson.

$2.$ List four example business problems provided in this lesson that require predictive modeling.

$3.$ Summarize the business application used in the hands$-$on demos in this Lesson. What is the main goal of the analysis?

$4.$ According to SAS, the analytics life cycle has three phases. Identify each of the phases and briefly summarize them.

$5.$ The hands$-$on practice demo in Section $1\mathrm{.}1$ is called $$Practice the Demo: Creating a Project and Selecting Data.$$ In the practice activity, you assign a Role of Target to the variable called Churn. What is a Target variable?

$6.$ The SAS software platform in these lessons uses distributed processing. What impacts will this have on your model results as you work with the software?

$7.$ The first essential data task is to divide $($or partition$)$ the data. Why is it important to partition the data? Be sure to address underfitting and overfitting in your response.

$8.$ Describe two problems that missing values may cause in our models.

$9.$ The hands$-$on practice demo in Section $1\mathrm{.}2$ is called $$Practice the Demo: Build a Pipeline from a Basic Template.$$ In the practice activity, you chose a starter template called $$Basic template for class target$$ for your Pipeline. Why is our Target variable Churn considered to be a Class Target?

$10.$ In the hands$-$on practice demo in Section $1\mathrm{.}2,$ what is the purpose of the Imputation Node in your Pipeline?

$11.$ Did you encounter any challenges in using the software? If so$,$ how did you troubleshoot?

$12.$ Have you used SAS before in a previous class and$/$or at work?

$13.$ Is there anything that you found particularly interesting, relevant, clear, or confusing? If so$,$ please let your instructor know this feedback so that future assignments can be improved