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"It is easier for me to believe in God than to believe in evolution."
"We tend to call seeking the "easier path" intellectual laziness -- but I guess that is a virtue in religious circles."

Not intellectual laziness but the application of Occam's Razor.

COMPLEXITY AND SIMPLICITY:
Occam's Razor states that one should not increase, beyond what is necessary, the number of entities required to explain anything

Occam's razor is a logical principle attributed to the mediaeval philosopher William of Occam (or Ockham). The principle states that one should not make more assumptions than the minimum needed. This principle is often called the principle of parsimony. IT UNDERLIES ALL SCIENTIFIC MODELLING AND THEORY BUILDING. It admonishes us to choose from a set of otherwise equivalent models of a given phenomenon the simplest one. In any given model, Occam's razor helps us to "shave off" those concepts, variables or constructs that are not really needed to explain the phenomenon. By doing that, developing the model will become much easier, and there is less chance of introducing inconsistencies, ambiguities and redundancies.
THOUGH THE PRINCIPLE MAY SEEM RATHER TRIVIAL, IT IS ESSENTIAL FOR MODEL BUILDING BECAUSE OF WHAT IS KNOWN AS THE "UNDERDETERMINATION OF THEORIES BY DATA". FOR A GIVEN SET OF OBSERVATIONS OR DATA, THERE IS ALWAYS AN INFINITE NUMBER OF POSSIBLE MODELS EXPLAINING THOSE SAME DATA. This is because a model normally represents an infinite number of possible cases, of which the observed cases are only a finite subset. The non-observed cases are inferred by postulating general rules covering both actual and potential observations.

For example, through two data points in a diagram you can always draw a straight line, and induce that all further observations will lie on that line. However, you could also draw an infinite variety of the most complicated curves passing through those same two points, and these curves would fit the empirical data just as well. Only Occam's razor would in this case guide you in choosing the "straight" (i.e. linear) relation as best candidate model. A similar reasoning can be made for n data points lying in any kind of distribution.

Occam's razor is especially important for universal models such as the ones developed in General Systems Theory, mathematics or philosophy, because there the subject domain is of an unlimited complexity. If one starts with too complicated foundations for a theory that potentially encompasses the universe, the chances of getting any manageable model are very slim indeed. Moreover, the principle is sometimes the only remaining guideline when entering domains of such a high level of abstraction that no concrete tests or observations can decide between rival models. In mathematical modelling of systems, the principle can be made more concrete in the form of the principle of uncertainty maximization: from your data, induce that model which minimizes the number of additional assumptions.

This principle is part of epistemology, and can be motivated by the requirement of maximal simplicity of cognitive models. However, its significance might be extended to metaphysics if it is interpreted as saying that simpler models are more likely to be correct than complex ones, in other words, that "nature" prefers simplicity.

Is it more faithful to Occam's Razor to think that a million monkeys typing randomly on a million typewritters over an infinite period of time would be successful in writing the collected works of William Shakespeare, or is it more faithful to Occam's Razor to think that there was an intelligent designer of these writings?

HUMAN LIMITATIONS:
Scientific empiricism can be a useful tool but it is flawed. Its reliance upon human experience is both its strength and weakness. All of the concepts of physics, chemistry, and all of scientific investigation are dependent upon sense perception. But sense perception is by its very nature, not totally reliable. Errors arise from the presence of what psychologists call thresholds. There are three such, the upper threshold, the difference threshold, and the lower threshold. These thresholds occur for all of the senses but to illustrate let's consider hearing. The lower threshold can be described as the inaudible sounds made by playing a piano whose keyboard has been extended in pitch downward beyond that, which is perceivable by the human ear. The strings do vibrate and sound waves are generated but they cannot be heard. The upper threshold is simply the same situation at the opposite end of the keyboard. The difference threshold can be described as two strings of the piano tuned to the same note. They sound identical when struck. But tones sound differently only when their vibrations vary by five or six per second. If these two string's vibrations vary by only one or two per second, technically they are not the same note even though the difference cannot be heard.

These thresholds of human sensory experience demonstrate that: 1) It is impossible for human beings to know nature absolutely, 2) Empirical evidence ALONE is insufficient grounds for knowing anything, 3) Any denial of the possibility of intelligent design based upon empiricism spotlights the antecedent assumptions of the one making the denial. If human sensory experience is so unreliable in such a mundane matter as the tones from a piano how much more unreliable might it be in more complex matters?