# Business modelling - Essay Example

Summary
There are so many models that can be used for this purpose. This paper will look at some of these models and their strengths and limitations.
This…

## Extract of sample "Business modelling"

Download file to see previous pages It also helps in reducing clustered and excessive data in a given setting to a manageable amount. It helps one to select on the precise variables that can be used in the study of managing a business. Therefore, it will help in making decisions of the business (Yao and Li 2013).
The variables in this technique helps in correcting certain mistakes that would otherwise been made in a normal business setting. For example, a business owner who thinks that extending business hours would certainly increase profits may re-think on this when they use the technique. This will go a long way in improving the business.
Linear regression is normally used with variables that are represented linearly. This will limit this technique to only data that are linear and cannot work with non-linear problems. The variables that are dependent are normally in a continuous form or they are close to being continuous, that is, they are able to be represented by any value. This linearity between dependent and independent variables will not always be true since some relationships have a curved kind of representation. For example, the relationship between age and income is not linear, but curved. Income increases during early years of a person and slows down as the age of the person proceeds (Fearn 2011).
Linear regression analyses the average in the relationship between independent and dependent variables. For example, when representing the relationship between the eating behavior of people and increase in their weight, this technique will represent the average weight of the food eaten with the change in their weight over time. This will not give a complete and clear description of the exact data that there is in a given situation hence there may be a misrepresentation of the data (Huang 2013).
Linear regression is normally affected with variables that are on the extreme. These variables are known as outliers. They are ...Download file to see next pagesRead More
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