As data continues to shape decision-making across the creative industries, the ability to analyse and interpret information has become an increasingly valuable skill for researchers in the fields of arts, communication, and digital media. Recognising this growing demand, the Statistical and Operational Research Consultancy and Education (SORCE) Unit under the School of Mathematical Sciences (SMS) organised a hands-on workshop titled “Exploring Data with SPSS: From Basics to Correlation Analysis.” This initiative reflects SORCE’s commitment to promoting statistical literacy and equipping students from diverse disciplines with practical data analytics skills.

Tailored Quantitative Training for Media Researchers

The one-day workshop, conducted by Dr Ang Siew Ling, was specially designed for postgraduate students and early-career researchers from the Arts and Social Media programmes. The workshop introduced participants to the fundamentals of quantitative data analysis using IBM SPSS. As one of SORCE’s educational initiatives, the workshop aimed to demonstrate that statistics is not solely a tool for mathematicians or researchers, but an essential component of evidence-based decision-making in creative industries, digital marketing, branding, communication, and content creation.

Mastering Data Fundamentals and Visualisations

Throughout the session, participants first learned how to organise and enter survey data into SPSS, distinguish between different types of variables—including nominal, ordinal, and scale data—and understand why selecting the appropriate measurement level is crucial before conducting any statistical analysis.

The workshop then explored descriptive statistics, where participants learned how to summarise data using measures such as the mean, median, standard deviation, and frequency distributions. Rather than focusing solely on statistical calculations, the session emphasised how these measures help researchers understand audience behaviour and identify meaningful patterns within datasets. Participants also learned how to communicate findings effectively through various visualisations, including bar charts, histograms, boxplots, and scatterplots, highlighting the importance of presenting data in a clear and visually engaging manner.

Assessing Survey Reliability and Relationships

Building on these foundations, Participants were introduced to reliability analysis using Cronbach’s Alpha, an essential technique for evaluating the internal consistency of survey questionnaires. Through examples related to social media engagement, participants discovered how researchers assess whether multiple questionnaire items measure the same underlying concept before drawing meaningful conclusions from the data.

The workshop also introduced correlation analysis and simple regression analysis, enabling participants to examine relationships between variables, such as daily hours spent on social media and levels of user engagement. Through guided SPSS demonstrations and scatterplot interpretation, participants learned how to evaluate the strength and direction of relationships while appreciating a fundamental research principle—that correlation does not imply causation.

Hypothesis Testing for Evidence-Based Decisions

To further enhance participants’ understanding of statistical reasoning, the workshop concluded with an introduction to hypothesis testing. Participants performed one-sample t-tests, independent samples t-tests, and ANOVA analyses to investigate research hypotheses. By focusing on the interpretation of SPSS outputs, p-values, and research conclusions rather than manual calculations, students gained confidence in applying statistical evidence to support decision-making and research findings.

Interactive Application and Real-World Analytics

The workshop adopted an interactive and application-oriented approach, with particpants actively entering data into SPSS, generating statistical outputs, creating visualisations, and interpreting results through guided exercises and discussions. Real-world examples drawn from social media analytics and digital communication enabled participants to appreciate how data can be applied to evaluate audience engagement, assess campaign effectiveness, and support strategic creative decisions.

SORCE’s Ongoing Mission for Interdisciplinary Growth

This workshop exemplifies SORCE@SMS’s mission to promote statistical knowledge beyond traditional mathematics disciplines by providing consultancy, training, and educational programmes that empower students, researchers, and industry practitioners to make informed, data-driven decisions. By bridging statistical analysis with practical applications in the creative and digital media sectors, SORCE continues to foster interdisciplinary learning and enhance graduates’ digital competencies.

Dr Ang Siew Ling
School of Mathematical Sciences
Email: @email