Workshops
STATISTICS FOR DESIGNERS: MAKING SENSE OF DATA
With the proliferation of sensors everywhere in our lives, the rate at which data is being generated seems out of control. The goal, of course, is not to amass data – it’s to make meaning of that data, a task that can often be elusive. This workshop is designed to help participants make sense of, and critique, the design of quantitative studies generated by others, and the results of those studies – marketing, engineering, medical or research and development groups. (Hint: not all studies are well designed.) It will also encourage the incorporation of quantitative methods into current design research activities.
These methods represent a change. The field of design, historically, has included little or no metrics. Incorporating quantitative research methods has a double benefit: 1) when conducted early in a design project, it informs the design team and steers the design work accordingly, revealing patterns of perceptions, attitudes and usability for various user groups that would otherwise have been missed, and 2) it adds credibility and confidence to design recommendations that could otherwise seem too far out and risky. The design team can be more assured in their directions, and more innovative by acting early on opportunities that may have otherwise been overlooked. This approach will especially enhance a team’s effectiveness in organizations and product categories in which evidence-based design will help ensure the team’s success. Even when it’s applied to small-scale studies of 8 to 12 people (the types accessible to design teams and doable within a fixed time and budget), data visualization and statistical analyses can be enlightening.
By the end of the workshop participants will have a better understanding of:
• How to ask proper questions, and identify improper questions
• The meaning of surveys (and the meaninglessness of some)
• Basic concepts in statistics – averages, means, standard deviations, probabilities and correlations
• How to interpret statistics being reported in design, marketing or engineering reports
• How to critique research reports
• The statistical significance of differences seen between two or more study groups (different designs, gender, age, geographic locations, or other categories)
• The significance and usefulness of small-scale studies, when they are appropriate
• How to predict the reactions of large populations by conducting small scale studies
• Methods for designing and conducting quantitative studies
Although the title states “designers,” this workshop is appropriate for, and open to, anyone looking to add or improve his or her knowledge in basic quantitative research methods.
To inquire about a workshop for your team, click here.