Question

You are working as the analytics developer for the National Weather Service, who has given you 50 years of data to analyze.

• Why is it important to use statistics/linear algebra technique is used to resolve the business problem using Python script?
• Give at least two different examples of use cases that can be solved using the Linear Algebra.

Answer 1

Solution:

It is useful and insightful to use the statistics or linear algebra to analyze this problem because the weather data for the previous 5 years will be extremely huge and the number of data points in the data will seemingly be high which will be difficult for a human eye to gauge and analyze. Hence, statistics provide us with tools that can be used to analyze the data which is big in volume, variety. Simply, the big data which is available with us for the analysis is the one which needs to be tackled using sophisticated statistical tools as well as linear algebra techniques which will help in coming out with insightful results in a short duration. Thus, it is important to use these techniques for the analysis of the data.

The use cases of linear algebra are found ubiquitously around us and are used widely across almost all the businesses around the world for coming up with better insights from the data that they have. The two most common use cases of linear algebra in the business environment are as follows,

• While predicting the probability of default by a person who has taken up a loan from the bank. The bank will use various parameters to predict whether or not the person will default on her loan amount. This helps banks in determining the amount of loan that they can provide to the consumers.
• While understanding the improvement in sales by understanding the number of marketing expenses put up by the organization. The linear algebra model helps in the determination of the reality of whether or not the advertising has impacted enough to increase sales.

These are two common use cases of linear algebra and statistics in the world of business.