Wondering what the answers are?

If you’ve got one of my business cards the answers are “wine” and “lettuce”.

Here are the others…

80/20 rule:

A principle for setting priorities on software features: users will use 20% of the features of your product 80% of the time. Focus the majority of your design and development effort (80%) on the most important 20% of the product.

2-second rule:

A loose principle that a user should not need to wait more than 2 seconds for certain types of system response. The choice of 2 seconds is somewhat arbitrary, but a reasonable order of magnitude.

3-click rule:

The principle that access to any feature of an application, or each logical step in a process, should require no more than 3 clicks – a helpful rule of thumb in trying to minimize the steps necessary to perform tasks. However, religious adherence to this rule, as with many others, is probably misguided.

The Magical Number 7 ± 2:

Miller’s Law another rule of thumb which tells that the number of objects an average human can hold in working memory is 7 ± 2.

Fitts’ Law:

T = k log2(D/S + 0.5), k ~ 100 msec. T = time to move the hand to a target | D = distance between hand and target | S = size of target | Broadly, Fitts’ Law can be applied by designers to suggest moving target buttons closer and making them larger for extremely commonly used buttons.

Hick’s Law:

(1) H = log2(n + 1). (2) H = Σ pi log2(1/pi + 1). H = the information-theoretic entropy of a decision. n = the number of equally probable alternatives. pi = the probability of alternative i for n alternatives of unequal probability. The time it takes to make a decision is roughly proportional to H, the entropy of the decision (the log of the number of alternatives), i.e. T = k H, where k ~ 150 msec. This can be used to make a time estimate for how long people will take to make a decision in using a user interface, such as choosing a menu item, choosing a tool, or selecting an item on a navigation bar. Cognitive modeling approaches such as GOMS apply this to making predictions of human performance.