Have you ever performed any kind of analysis on the collected data? Yes, you might have done this in your university while working on your dissertation. If this is the case, you might know about different analysis techniques. Multiple regression analysis is one of the famous data analysis techniques many researchers use to draw valuable information. This technique is also used to understand the relationship between independent and dependent variables.
Along with this, there are many other advantages of multiple regression analysis. Today’s article is all about this type of data analysis. There will be a mention of its advantages and uses in detail. Before moving on further, let’s define it first with the help of examples.
What Is Multiple Regression Analysis, And Why Is It Important?
Multiple regression analysis is a statistical technique applied to datasets to know the relationship between several variables. It is a reliable method of knowing which variables have an impact on the topic of interest. This process of performing an analysis lets you identify which variables in the research matter the most. You also identify which factors can be ignored and how other factors influence each other.
This type of analysis is important in research. It is because it assesses the strength of the relationship between different variables. Different variables can be both dependent and independent. It also assesses the relationship between some predictor variables. Many students who don’t get any idea about variables, prefer to buy dissertation online to get this analysis done. Thus, this analysis leads to a more precise and accurate understanding of the association of each variable with the outcome.
What Are Some Examples Of Multiple Regression Analysis?
Many researchers use this analysis to predict or forecast the future. It is not only restricted to the education industry. Nowadays, every industry and department use this analysis. Some examples of this analysis in different industries are as follows;
Healthcare Example:
You are a biostatistician working on a medical research project. You want to devise a method for predicting a child’s future height. Environmental influences and a child’s diet are two separate variables influencing a child’s growth. Multiple regression analysis can be used to predict a child’s future height if the coefficient values of these factors change. Hence, this one example elaborates the use of this analysis in the healthcare field.
Business Example
You hold stock in a publicly-traded company and wonder if now is the time to sell. The company’s profitability, costs, competition, and assets are all factors that could influence the stock price. You can use these four independent factors to run a multiple regression analysis. Based on its results, you can decide whether you should sell it or not.
What Are The Advantages Of Multiple Regression Analysis?
Like every other regression model, the multiple regression model also has some advantages and disadvantages. This article will only talk about the pros of this analysis. Hence, a brief description of the major advantages is as follows;
Predictive Analytics
It is the most popular advantage of multiple regression analysis. With the help of this analysis, you can make predictions about future risks and opportunities. In a business research, you can use it to predict future demand and supply predictions. Using some advanced statistical formulae, you can also predict the number of shoppers that will shop for the product in the near future. Hence, it is one major advantage of this analysis.
Operation Efficiency
The second advantage of regression analysis is for businesses. In business research, companies use this analysis to know about their performance. It can also be used to optimise the performance of the factory. For example, you can use the variable oven temperature to know about the shelf life of your product. At what temperature you can have the maximum shelf life of your baked products. All this can be done using multiple regression analysis. It is because you will be measuring the relationship of the two variables, i.e., oven temperature and shelf life.
Support Decisions
Regression analysis is all about predicting the future and finding the relationship between different variables. Once you have done this, it allows you to make decisions based on your findings. It adopts a scientific angle to see the impacts of variables on the topic of your study. With this angle, there will be multiple solutions in front of you. All you need to do is choose one from them and implement it for better results in future.
New Insights
With its powerful predictive ability, it provides new and fresh insights into the topic of your study. Many researchers gather a lot of data and process it through multiple regression analysis. After completing the analysis, they get multiple solutions in front of them. Those solutions are basically the new insights. The researchers can use those solutions by getting masters dissertation help to solve the problem at hand in a better way.
What Are The Uses Of Multiple Regression Analysis?
Certainly, along with advantages, there are uses of this analysis. From the discussion, you might have known about the popularity of this method. Now, let’s look at some of the uses of multiple regression analysis.
- Researchers use this method to obtain trustworthy regression results. Those results can help them predict the future with much more precision.
- It can be used to make correlations between different variables. Those correlations explain the relationship of variables with each other in a better way. It is also used to make informed decisions based on its outcome.
- As a researcher, you can also use this analysis to control the independent variables. You can change the independent variable until you get your desired results.
- One of the most important uses of this analysis is that you can analyse as many relationships as you want. You just need to change the variables, make new relations, and analyse them.
Conclusion
All in all, multiple regression analysis is a very helpful technique using which you can relate different variables. The relationships, as a result, can be used to make informed decisions and for many other purposes. The advantages mentioned above can help you understand the importance of this analysis.