For many, statistical analysis is something they never think about. They assume it is an area of study for math majors so that they can eventually become math professors.
However, statistical analysis plays a much bigger role than that. If you have a chance to pursue a Master’s in Applied Statistics, you should take the opportunity to do so because this subject applies to many areas of business and can lead to an excellent career.
What is statistical analysis?
In a nutshell, statistical analysis is the process of collecting and analyzing data to identify trends. Businesses use it to predict what will happen in the future so that they can plan accordingly, identify opportunities and prepare for upturns or downturns in the economy.
Imagine, for example, a business that has factored in weather predictions based on statistical analysis. From existing data samples, they can see that the coming years will have hotter and hotter summers, and certain regions will not get enough rain for bumper harvests.
How does this impact production? Does it affect the supply of raw materials that they use for production? Does it give the business an opportunity in another area, perhaps manufacturing products that help people deal with sweltering summers?
The business can predict where challenges lie in the future and also prepare for upcoming opportunities.
Any business that hopes to survive well into the future does this type of statistical analysis. That is why you cannot go wrong with a Master’s in Applied Statistics from an institution such as Michigan Tech. Many employers are looking for people who can model data and come up with predictions.
You can read this post for more reasons why you should learn statistical analysis.
Data analysis vs. statistical analysis: what is the difference?
To the layman’s ear, they may sound the same, but they are in fact different disciplines. Statistical analysis uses statistical modeling on data samples to get an insight into whole populations.
Data analysis is all about analyzing every single piece of data and then drawing conclusions that anyone can understand.
Examples of statistical analysis in business
- Hospitality – If you own a chain of hotels, sampling and analyzing data annually tells you when visitors peak and when they ebb. You can plan when to hire new staff and look for additional food and drink suppliers.
- Soft drink manufacturers – Companies that sell soft drinks don’t have to know how many individual units they can sell every year in every region. By using statistical analysis, they can predict sales based on past occurrences.
- Car manufacturers – As environmental issues peak, car manufacturers have adjusted production based on statistical sampling. They look at a cross-section of data to know where they should focus their efforts.
- Online business – Statistical analysis is a big predictor for online commerce. By sampling a small amount of data, sellers can predict which goods are trending and when they can expect a surge in sales. Towards Data Science explains how online vendors can streamline sales using statistical analysis.
Conclusion
Statistical analysis is a much-needed science for business. As long as you pursue an applied statistics degree from an accredited university, you will be sought after by employers. If you do your job right, you will make reliable statistical predictions, and you will be rewarded.