Contents
- 11.1 Look at the data
- 11.1.1 Fitts’ Law—jumping to the numbers
- 11.1.2 But I did a regression …
- 11.2 Visualise carefully
- 11.2.1 Choice of baseline
- 11.2.2 Choice of basepoint
- 11.3 What have you really shown?
- 11.3.1 Think about the conditions
- 11.3.2 Individual or the population
- 11.3.3 System vs. properties
- 11.3.4 What went wrong?
- 11.4 Diversity: individual and task
- 11.4.1 Don’t just look at the average
- 11.4.2 Tasks too
- 11.5 Mechanism
- 11.5.1 Quantitative and statistical meet qualitative and theoretical
- 11.5.2 Generalisation
- 11.5.3 Example: mobile font size
- 11.6 Building for the future
- 11.6.1 Repeatability and replication
- 11.6.2 Meta-analysis and open scholarship
Glossary items referenced in this chapter
ACM conference, ANOVA (Analysis of Variance), base period, baseline, basepoint, borrowed methods, CHI conference, claims analysis, constant area visualisation, controlled environments, controlled experiment, Pearson correlation coefficient, data analyst, data consumer, data journals, day effects, dependent variable, design space, ecological validity, effect size, emergent patterns, empirical data, error rate, expert evaluation, extrapolation, extreme values, false baseline, false origin, file tree visualisation, fine positioning tasks, Fitts' Law, fixed effect, font size, generative artefact, in-the-wild, independent variable, index of difficulty (IoD), inter-related factors, interpolate, linear regression, mechanism, menu navigation, meta-analysis, model, multiple causes, open situations, p-value, peripheral vision, PieTree, pointing tasks, presidential inauguration, public domain, public sector borrowing, qualitative methods, quantitative data, R, random effect, regression analysis, repeatability, replication, RepliCHI, response time, sample-based approaches, scatter plots, sensitivity, single cause, SPSS, statistical analysis, statistically significant, statistically significant results, Student's t-test, subjects, target size, task completion time, tasks, temporal data, theoretical understanding, TreeMap, variability, visualisation