National Workshop on Data Analysis through SPSS

Start Date: 
Monday, 20 December 2021
Start Time: 
(All day)
Computer Lab D



20th -24th DECEMBER 2021

The Department of Economics of IIS (deemed to be University) organized a five-day National Workshop on DATA ANALYSIS THROUGH SPSS from 20-24 December, 2021. It was attended by 44 participants including students, research scholars and faculty members. Each day of the workshop consisted of four sessions from 10 am to 3 pm with intermittent breaks for a refreshing breakfast, lunch and tea.

The first day of the workshop began with a welcome note by Dr. Anima Vaish, Organizing Secretary of the workshop. She also introduced the resource person of the workshop, Dr. Anurag Asawa, Associate Professor of Economics at Gokhale Institute of Politics and Economics (Deemed to be University), Pune. Dr. Ashok Gupta, Hon’ble Chancellor, IIS deemed to be University, welcomed the resource person by presenting a memento to him. Dr Gupta further emphasized on the growing importance of Data Analysis and use of SPSS in various arenas of academics and research. He then invited Dr Asawa to take over.

Dr. Asawa started with a brief introduction of self and an introduction to data analysis through various statistical tools. SPSS has become very popular software among academicians and researchers for data analysis nowadays due to its easy to handle and interactive interface. He briefly described the plan of the workshop and how it would help in building the foundation of analyzing data using SPSS. With this, the inaugural session came to an end and was followed by refreshments.

After refreshments, other sessions for the first day commenced, which covered topics like linkages between the statistical tools and the data with the help of real-life examples, Measurements of Scale, Measures of Central Tendency, Classification of variables, Hypothesis Testing and tests such as F-test, T-test, Chi-square tests, etc. In the last session, Dr. Asawa demonstrated the use of various functions such as files, labels, values, etc, of SPSS.

Day 2 was dedicated to teach the participants the application of different tests based on the nature of the variables under different situations in case of univariate analysis and bivariate analysis.The concept of P-Value (Probability value of committing error) and test of normality via Kolmogorov-Smirnov statistical test were next explained by using some real-life examples The focus of other sessionswas on parametric tests -‘one sample t – test’,Independent Sample t-test and Levene’s test for equality of variances.

The focus of Day 3wason paired sample t-test. The resource person, after a quick recap of the topics covered in the previous day, introduced-One way ANOVA which is used to find the effect of two or more groups of independent variables on one dependent variable, along with some practical examples. This was followed by introduction of the graphical aspect of the data analytics including Boxplot, which was later followed by the analysis of cross-classification using Cross tabs.

As the foundation of SPSS was built in the three days, the focus of Day 4 of the workshop was on non-parametric tests like Wilcoxon signed rank test, Mann-Whitney and Wilcoxon rank – sum test, Mann-Whitney U test, Wilcoxon Rank-Sum test, Kruskal-Wallis H Test and Friedman’s ANOVA along with their significances and uses. One-way ANOVA is used to test the differences between several related groups. Although in case of violations of its assumptions, there is another alternative to the repeated-measures case: Friedman’s ANOVA.

On the last day of the workshop, the resource person discussed some advanced topics in SPSS namely, Principal Component Analysis (PCA) and Factor Analysis (FA). Multivariate analysis is the technique of analysis of data consisting of observations pertaining to a reality involving two or more variables.Factor Analysis is a parametric procedure used to analyse interrelationships among a large number of variables. The session also emphasised on the violation of assumptions of the classical linear regression model- the problems of multicollinearity. Dr. Asawa dealt with the consequences, detection and remedial measures for this problem.

The workshop drew to a close with a few participants sharing their experiences and insights and thanking the resource person for elucidating the concepts with such innovative examples. Finally, Dr. Anima Vaish concluded with a formal vote of thanks. The workshop thus proved to be a great learning experience for all the participants.