Question

Answer the questions provided. This module describes ways where unexpected errors could ensue when performing multiple regression. In your own words (easy words, not difficult one), describe such potential errors. What are some ways to respond to such pitfalls? In addition, describe ways to prevent such pitfalls during data collection.

Answer 1

ANSWER:-

   Regression analysis is a widely used statistical technique;  

It helps investigate and model relationships between variables.

  * It helps investigate and model relationships between variables. It also uses a derived model to predict a variable of interest. The potential applications of regression analysis are numerous and can be found in almost every field including economics, biology, management, chemical science and social science.

* Applying regression does require special attention from the analyst. Each process step from model specification and data  collection, to model building and model validation, to interpreting the developed model needs to be carefully examined and  executed.

*  A small mistake in any of these steps may lead to an erroneous model. This article describes some common mistakes made in regression and their corresponding remedies.  

* Regression analysis indicates a strong relationship between two variables, they are not necessarily functionally related. Any two sequences, y and x, that are monotonically related (if x increases then yeither increases or decreases) will always show a strong statistical relation.

*  A functional relationship may not exist, though. For example, a strong statistical relation may be found in the weekly sales of hot chocolate and facial tissue. But this does not necessarily mean that hot chocolate causes people to need facial tissue or vice versa.