Lab 10

Today in the lab, we used Excel to figure out the probabilities of the grade distribution in a class. In order to find these probabilities, we had to first write algorithims to return the correct grades pending on a student's test score. Luckily for me, I took K201 in the fall and have had experience working with Excel so I found this task to be very easy. We also learned about the Shannon and Harltey measure of probability and information. The Shannon measure is a lot more accurate and precise. The Hartley measure is almost an average and will return the same number no matter how many numbers you are trying to find the Entropy of.

Data Analysis

In Friday's lab, we learned how to use Excel to analyze large groups of data. I'm currently in Finite mathmatics and we have been studying linear models and graphs. There are equations to finding slopes of equations as well as other information. With the aid of Microsoft's Excel however, these functions can be performed much more easier. Actually, with Excel, you can figure out even more information in the time of a couple clicks, such as Coefficiants, Intercepts, and etc.

Intro to Statistical Analysis using Excel

Today in the I101 lab, we became familiar with using Microsoft Excel and Statistical Analysis. I took K201 during the fall so I have used Excel before. I actually became quite good at using it so I'm confident in my Excel skills. In the lab, we played around with graphs and histograms. I've attached an image of my histogram from the lab.

Binary Numbers

We recently learned about binary numbers. Binary numbers is a language read by computers using only 1's and 0's. While we define the number seventy eight as 78, a computer reads it as 1001111. Weird huh? It's somewhat of a confusing process. To convert a regular number to binary, it helps to start with a table of sorts. You start at the right and work you're way to the left with:

2^0, 2^1, 2^2, 2^3....and so on until the largest number cannot go into whatever number your trying to convert. For the number 529, I would go all the way up to 2^9 which is 512. Since 512 will go into 529 once, the first number is a 1. You're left with 17 and you see how many times it can fit into the remaining numbers. 17 does not fit until 2^4 (16), so you subtract 16 from 17, leaving 1. Then you continue seeing how many times 1 fits in the remaining numbers. So 529 converts to 1000010000. To convert a a binary number into regular, you just do the reverse process. Its tricky, but it can be mastered.

My First Experience With Unix

We recently worked with Unix in my Informatics Lab. Basically, it is a very basic and ancient form of operating systems such as Windows or whatever Mac runs. Windows allows users to perform tasks and makes them simple by clicking on objects and so on. What Unix does is performs the tasks with the exception that you can't actually see the action take place. It's all done by text.

Some of the commands I learned were:

rm - which removes a file, much like clicking on or deleting a file in Windows
clear - which clears whatever is on the screen, much like minimizing or exiting programs to go back to the desktop and starting with "a clean slate".
more - provides more text or information, much like scrolling down a webpage or document with a mouse to see more of something.
cal - provides a calendar much like using Microsoft Outlook's calendar or the calendar on the desktop/toolbar in Windows.

Modeling The World

I felt the "Modeling the World" lecture/notes were interesting, yet too in depth. I would think it is commmon knowledge what a model is. For instance...a model car...it is just that. Its a miniture car modeling the bigger version of it. Models are used to simply and act as something. I felt the lecture and notes were very in depth on the subject, but maybe it will be beneficial when we tackle later lessons and what not.

My Attempt at Using HTML

The Ideas Behind Signs and Symbols

I felt the lecture on the semiotics was both somewhat interesting yet common knowledge. It's somewhat obvious that a common group of people or a general consensus must agree on a symbol to mean something.

I felt the Information Theory and the Bit section of the lecture was:

• Confusing
• Hard to Understand
• and Probably Very Informative

As always, don't forget to check out infoport.blogspot.com