SPSS Regression for Right Data-Driven Decisions

SPSS Regression is a powerful tool for discovering hidden relationship in your data. As business technology has advanced exponentially in recent years, data-driven decision making has become a much more fundamental part of all sorts of industries and involves making decisions that are backed up by hard data rather than making decisions that are intuitive or based on observation alone.

Making data-driven decisions means a lot of number crunching. However, the good news is that you likely don’t have to do the number crunching yourself, but you do need to correctly understand and interpret the analysis. We already discussed the important role of Forecasting and Predictive Modeling in driving a company’s success. Let’s have a look now at another important type of data analysis techniques Regression Analysis.

What is Regression Analysis?

Suppose a record company was interested in predicting album sales from advertising. There are many factors that can impact the sales number from the amount spent promoting the album before release, how many times songs from the album were played on the radio in the week before release and how attractive people found the band’s image.

Regression Analysis is a set of statistical processes that mathematically estimate which of those factors does have an impact. It answers the questions: Which factors matter most? Which can be ignore? How do those factors interact with each other? And, perhaps most importantly, how certain are we about all of these factors? In regression analysis those factors are called variables. You have your dependent variable — the main factor that you’re trying to understand or predict.

In the example above, the dependent variable is album sales. And then you have your independent variables — the factors you suspect have an impact on your dependent variable. More specifically, regression analysis helps one understand how the typical value of the dependent variable changes when any one of the independent variables is varied, while the other independent variables are held fixed.

One of the most popular software for Regression Analysis is SPSS Regression add-on module. It has great advanced functionality

SPSS Regression’s advanced functionality includes:

• Binary Logistic Regression • Logit Response Models • Multinomial Logistic Regression Nonlinear Regression • Probit Response Analysis • Two Stage Least Squares • Weighted Least Squares

How do companies use SPSS Regression?

Regression analysis is the go-to method in analytics and companies use it to make all sorts of business decisions. Like extracting information from existing data sets to determine patterns and predict future outcomes and trends. Or building regression models to optimise business processes.

Over time businesses have gathered a large volume of unorganized data that has the potential to yield valuable insights. However, this data is useless without proper analysis. Regression analysis techniques can find a relationship between different variables by uncovering patterns that were previously unnoticed.

At OLSPS Analytics we have a wonderful team of experienced professionals skilled in different technologies like Big Data, Analytics, AI, ML etc, specialising in making sense out of data. If you are looking to explore the SPSS Regression add-on module, contact us for a free trial version.

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