Applying regression on secondary data using SPSS

By Riya Jain & Priya Chetty on March 10, 2022

Regression is a versatile statistical test used to understand and quantify the relationship between two or more variables. It is popularly used in secondary and primary data. It helps to not only understand past trends but also predict the future.

However, before applying a regression model it is important to check the correlation between the variables first. The previous article explained how to perform correlation tests on secondary data using SPSS. This article will explain the application of regression tests on secondary data using SPSS, using the same dataset.

Case description for regression test on secondary data using SPSS

In the previous article, it was shown that there is a correlation present among India’s Gross Domestic Product (GDP), unemployment rate (UNE) and population growth (POPG) for the period 2012-18. This article explores the extent of the impact of UNE and POPG on India’s GDP.

Accordingly, the hypothesis is:

Null hypothesis (H0): There is no relationship between unemployment rate, population growth and economic growth of India for the period 2012-2018.

Follow the below steps to perform the regression.

Step 1

Perform the correlation test as shown in the previous article.

Step 2

Run the regression test. For this, click on ‘Analyse’, then ‘Regression’, then ‘Linear’ as shown below.

The following window will appear. From this window move the natural log-transformed variable LnGDP to Dependent followed by LnUNE and LnPOPG to Independent(s).

Step 3

Click on ‘OK’. The following output window appears for regression analysis.

Interpreting the results showing the impact of population growth and unemployment on India’s economic output

The above figure shows the output of the regression test. It has many values. Each must be interpreted independently before deciding whether to accept or reject the null hypothesis.

In the case of this example, the values of R square and adjusted R square are 0.98 and 0.97, depicting that about 97% of the variation in the economic growth of India is represented by unemployment growth and population growth. This is a favourable result. The F value is 292.70, which is also favourable since it is more than 1. It denotes that there is more precision in the model due to the independent variables. The significance ‘Sig.’ value is 0.00. The significance value should always be less than 0.10 in order to prove that an impact is present. Since in this case, it is meeting the criteria, we can conclude that the unemployment rate and population growth rate rise has an impact on the economic growth of India.

Priya is the co-founder and Managing Partner of Project Guru, a research and analytics firm based in Gurgaon. She is responsible for the human resource planning and operations functions. Her expertise in analytics has been used in a number of service-based industries like education and financial services.

Her foundational educational is from St. Xaviers High School (Mumbai). She also holds MBA degree in Marketing and Finance from the Indian Institute of Planning and Management, Delhi (2008).

Some of the notable projects she has worked on include:

• Using systems thinking to improve sustainability in operations: A study carried out in Malaysia in partnership with Universiti Kuala Lumpur.
• Assessing customer satisfaction with in-house doctors of Jiva Ayurveda (a project executed for the company)
• Predicting the potential impact of green hydrogen microgirds (A project executed for the Government of South Africa)

She is a key contributor to the in-house research platform Knowledge Tank.

She currently holds over 300 citations from her contributions to the platform.

She has also been a guest speaker at various institutes such as JIMS (Delhi), BPIT (Delhi), and SVU (Tirupati).

I am a master's in Economics from Amity University. Having a keen interest in Econometrics and data analysis, I was a part of the Innovation Project of Daulat Ram College, Delhi University. My core expertise and interest are in environment-related issues. Apart from academics, I love music and exploring new places.