Deductive reasoning works from the more general to the more specific. Inductive reasoning works the other way, moving from specific observations to broader generalizations and theories.
These two methods of reasoning have a very different "feel" to them when you're conducting research. Inductive reasoning, by its very nature, is more open-ended and exploratory, especially at the beginning. Deductive reasoning is more narrow in nature and is concerned with testing or confirming hypotheses. http://www.socialresearchmethods.net/kb/dedind.php
In statistics that means deductive reasoning is measuring something like the fit of a regression line to known data, and using it to determine other probable data points within the bounds of the known data. Inductive reasoning would be using that information to project the regression line to an unknown point – e.g. forecasting a trend.
It is always less accurate (more inherent error) to induce than to deduce additional points from any given set of data. Further, while the degree of error within a data set will not change for inductively reasoned possible points, it increases non-linearly with inductively reasoned points. That is, the further away a projected point is from the actual data set, the larger the amount of error that must be recognized in the result.