use the below textbook reference and answer the following questions

use this Textbook Title: Predictive Analytics for Business Strategy

Subtitle: Reasoning fro Data to Actionable Knowledge

ISBN: 9781260084641

Authors: Jeff Prince

Publisher: McGraw-Hill Education

Publication Date: 2019

Assigned Readings:

Chapter 10. Identification and Data Assessment

Overview:

Chapter 10 introduces the concept of identification and explains how to assess data through the lens of its ability to identify a parameter(s) of interest. It explains that an understanding of identification is crucial when trying to estimate the effect of a treatment on an outcome. Next, two common situations are highlighted in which identification problems often arise: attempts toward extrapolation/interpolation, and data with variable co-movement. For both of these circumstances, alternatives are discussed for remedying the corresponding identification problem. Finally, the unfortunate case in which an identification problem exists in the form of endogeneity and cannot be remedied is addressed.

Learning Objectives:

After studying this chapter, you should be able to:

1. Explain what it means for a variable’s effect to be identified in a model
2. Explain extrapolation and interpolation and how each inherently suffers from an identification problem
3. Distinguish between functional form assumptions and enhanced data coverage as remedies for identification problems stemming from exploration and interpolation
4. Differentiate between endogeneity and types of multicollinearity as identification problems due to variable co-movement
5. Articulate remedies for identification problems and inference challenges due to variable co-movement
6. Solve for the direction of bias in cases of variable co-movement