Shannon and Hartley

The difference between Hartley and Shannon is that the Hartley measures the amount of information needed to remove the uncertainty but Shannon measures the average amount of information needed to remove uncertainty. To measure information using Hartley, you have to use the Hartley function which is: H(A)=log₂|A|. A equals the number of choices. Shannon's Entropy uses the probability of occurrence and uses a different equations.

Inductive Modeling

After lab 9, I realized that algebra is useful when calculating statistics. I learn that by using the linear equation, I can find the linear regression of the data I have in front of me. Also, I learn that mean, median, and mode are useful when looking at statistics.
Inductive modeling is useful, when studying a sample of a large number of something. With the information gathered from inductive modeling, one can find ways to improve others lives. Inductive modeling helps us find evidence that answers our question, however, we are not certain about the answer. Inductive modeling gives us the satisfaction of having an answer instead being in a state of not knowing.