“I would have missed that in R,” she muttered.

Silence on the line. Then: “You’ve been holding out on me. Last I heard, you were fighting with R.”

She saved the SPSS project file (.sav) and exported her output as a Word document (.docx) with one click. File > Export . The tables were perfectly formatted. No copy-pasting disasters. No “Error: object 'data2' not found.”

Before leaving, she ran one more test—a nonparametric Mann-Whitney, because one reviewer always asked about normality. SPSS handled it in two seconds. She added a footnote: “All analyses performed using IBM SPSS Statistics (version 29).”

At 1:15, she discovered something unexpected. She clicked Graphs > Chart Builder . Within three clicks, she had a clustered bar chart comparing recovery rates across treatment groups and hospitals. Color-coded. Labeled. Publication-ready.

She didn’t care about the brand. She didn’t care about the GUI. She cared that a grad student in Bangladesh, a rushed clinician in Chicago, or a tired researcher at 11 PM could sit down, click a few menus, and find a p-value that might save lives.

Aliyah double-clicked the icon. The interface opened—clean, almost boring. No command line. No cryptic error messages. Just menus: Analyze > Compare Means > Independent-Samples T-Test .

Her phone rang ten minutes later. It was her old PhD advisor. “Aliyah, I saw the draft. Did you run the mixed model for the repeated measures? Remember, week 2 to week 6—”