Week 2: Design Types, Variables and Scales
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13 Terms
Aims to discover ideas and themes. The design stays flexible so new facets can emerge.
On campus: you do not yet know why one quadrangle is busy and the near identical one beside it is empty, so you observe and ask open questions to find out.
Tests a specific hypothesis through pre planned, rigid data collection.
On campus: you now suspect shade is the reason, so you design a study to test whether position choice tracks shade availability.
You deliberately impose a condition, then compare outcomes. The only design that isolates cause.
On campus: placing two different signage types on matched waste stations and comparing segregation accuracy.
You observe variables as they already exist, without manipulating anything. Used when control is impossible or unethical.
On campus: almost every study in this class. You cannot assign students to classrooms, but you can record how reported comfort varies across the rooms they are already in.
The explanatory variable, the one a designer would manipulate.
On campus: ventilation type of a classroom, signage type at a bin station, surface material of a walkway.
The outcome that depends on the independent variable.
On campus: reported thermal comfort, segregation accuracy, observed use intensity.
A factor unrelated to your purpose that nonetheless affects the outcome and introduces error.
On campus: an examination week, a sudden downpour, a cancelled class emptying the corridor you were counting.
Categories with no order.
On campus: programme of study, waste category, entrance used, mode of arrival.
Ordered categories with unequal or unknown gaps between them.
On campus: a comfort rating from 1 to 5. The gap from 4 to 5 is not necessarily the gap from 1 to 2.
Equal gaps, arbitrary zero, so ratios are meaningless.
On campus: temperature in degrees Celsius. Zero does not mean an absence of temperature.
Equal gaps with a true zero, so all arithmetic works.
On campus: dwell time, illuminance in lux, distance in metres, headcount, decibel readings, waste mass. Most of your data will be ratio level.
Interval and ratio together. Discrete if counted, continuous if measured.
On campus: people entering a door is discrete. The time they stayed is continuous.