Developing MY Voice.

That's problem one. Problem two will be based on a suggestion Mr. K made about the probability of being drafted. I don't think we ever actually did a question of it though...

Timeline:

By May 25th I will have completed my questions. By June 3rd, I will have filmed portions to be embedded in a prezi presentation. By June 6th, I will have completed my prezi and published it to the blog.

Personal Finance... YEA!

Alright, let's get this started with a concept I was stumbling with for a bit. I could not, for the life of me, understand why the formula for the feasible financial capital percentage one should consider when purchasing a home. For your information, the absolute maximum feasible percentage of one's income that should go towards their home is 32%. Here's a couple things to remember.

It's called the GDSR, and it's composed of a number of things. You've got your Monthly Mortgage Payment, your Monthly Property Tax Payment, your Monthly Heating Bill, and half of your Condo/Strata Fees. Now you lump that all together into one great big chunk and you divide it by your Monthly Income. The number that is generated will be a decimal, in theory. Technically, if you were using this formula on a house WAY out of your range, you'd get a whole number. Or, over 100% of your monthly income would be going to your house. 
That's right! The decimal you receive is a percentage! And that is the percentage of your income that is going to your house. You want that to be under 32. The formula looks like this:

Perhaps you are thinking, "That's all well and good, but what if I'm missing a variable, smart-guy!? Maybe I don't know my monthly mortgage payment, JERK!" Well fear not my fine, feathered friend. If you find 32% of your income, and subtract from it what you DO know, your answer will be what remains of your 32% income, or, what you have at your disposal for whatever variables you are missing. For example:

If I have $1000 a month for housing, my feasible income percentage will be $320. Let's say it's a house, BOO-YEA, no condo/strata fees. Heating is %40 a month, property taxes are $60. BEAR WITH ME.... $40+$60 is $100, Therefor... $320 - $100 = $220. I have $220 to spend on housing per month.

The other thing we covered today was the pros and cons of home ownership. For more information contact your local "Personal Finance" tagged slide... uh..(s)... Slides.

Statistics Reflection

Well here we are, at the end of another unit.

And as one might expect, the trip here wasn't easy. For example, I'm still not clear on how to create a histogram. I know I have to put the data in List One, I know I use Zoom Stat in the 2nd Trace menu, and I know I have to select the bar-ed graph from the stat plot menu, and put L1 in the top section and L2 in the bottom section. Unfortunately for me, I haven't a clue what goes in L2. Furthermore, it doesn't appear to be in any of the slides. or any of the scribe posts. I checked more than once. Damnit.

Also, I missed the class on Confidence Intervals and Margins of Error. Thankfully, the process by which they are found is simple enough. Confidence Interval is merely 1.96 σ above and below the mean. Easily expressed as (µ-1.96σ, µ+1.96σ). Likewise, Margin of Error is calculate by (1.96σ)÷(# of trials). For instance, if you had 100 trials with a standard deviation of 10 and a mean of 50, you'd have a confidence interval of (50-1.96(10), 50+1.96(10)), or (30.4, 69.6). The margin of error would be 19.6÷100, or 0.196. Also known as 19.6%

the problem I had with these concepts is the meaning of "Confidence" in this context. My assumption was that if the data was within the confidence interval, I could be confident in the probability of that occurrence. Not so. In fact, all it says is that, were I to repeat the experiment, 19 times out of 20 I'd be likely to find 95% of the data lying between the aforementioned interval. To reuse my previous example, 19 times out of twenty, 95% of the data of an experiment which (when previously tested) resulted in the data µ=50, #trials=100, and σ=10 would lie between 30.4 and 69.6.

MAN AM I TIRED.

Alright childrens, here's some things you should consider.

IMPORTANT CONCEPTS

1. When grouping, it is important to understand that patterns are more important than details. For example, if you had two tons of fruits, all different kinds, and half of your fruits were rotten... You want to group those and get rid of them. Whether or not it's an apple or an orange can wait, honestly!

2. When measuring how extreme a particular piece of data is, find it's distance from the mean in standard deviations! For example, If there are twenty cars on the road, and the mean speed of the cars is 50 mph with a standard deviation of two mph... Well, let's just say that if one of those cars is flying down the road at 60 mph, that'd be a little extreme! *note: 50-60 with standard deviation of 2 is a 5x(standard deviation) difference! Five standard deviations, in relation to road speed, is too dang fast!

3. REMEMBER! There are two ways to find Standard Deviation! There's a sample version and a population version. The most pronounced difference is that to find the Standard Deviation of a sample, you divide by n-1 instead of n! 

Well. Those are a few concepts we should consider for next class. I'd go into more detail, but I'd rather wait until I have a firmer grasp of this unit, I wouldn't want to sabotage any of you folks.

THE NEXT SCRIBE WILL BE PHONG, BECAUSE HE CAN SAVE US ALL.

Matrices Introduction: February 3rd, 2009

Let's start with a definition. "Matrix - (mathematics) a rectangular array of quantities or expressions set out by rows and columns, treat as a single element and manipulated according to rules." (courtesy of "thefreedictionary.com").

To elaborate, a matrix is always either rectangular or square, has a title (usually a single letter), and its name is derived by the title followed by the number of rows, followed by the numbers of columns.

For example:

A [1 3 -5 9] is named A, 1x4. The title of the matrix is "A", while it has one row, and four columns.

Similarly, each number (element) in the matrix is assigned an "address". The address is the lowercase letter of the matrix title, followed by the position in the rows, followed by position in the columns.

For example:

F [4 7 3 -11] is composed of:

f1,1... (4)

f1,2... (7)

f1,3... (3) and

f1,4... (-11)

Here is another matrix, with numbered columns and rows.

A 1 2 3

1[ -11 66 43]

2[ 4 74 22]

3[ 5 9 18]

4[ -8 12 -1 ]

5[ 15 -9 15]

This matrix is a 5x3 matrix, and as an example, the element found at "a 4,2" is 12.

In addition to these conventions, there are rules for matrix addition and subtraction.

Rule 1: The matrices must have the same dimensions. (such as being 1x4 + 1x4, or 8x2 + 8x2, or what have you.)

Rule 2: Matrices are added by simple addition (as well as subtracted through simple subtraction) of the respective elements on each matrix. Allow me to explain.

A [4 5 -1 -19] + T[-14 7 -3 8] is added thusly...

a1,1 + t1,1

a1,2 + t1,2

a1,3 + t1,3

a1,4 + t1,4

And the resultant matrix would appear [-10 12 -4 -11], and its title would be an arbitrarily assigned number or symbol, in context, hopefully one with some meaning.

Furthermore, there is an additional type of matrix I would like to explain. The Identity Matrix. The identity matrix is composed entirely of zeros and ones, because any number add or subtract zero is itself, while any number multiplied or divided by one is itself. Also, the identity matrix has only ones along a diagonal, with only zeros on either side. It may look something like this.

[1 0 0 0]

[0 1 0 0]

[0 0 1 0]

[0 0 0 1]

In closing, everyone please check the Digital Ethics post so that tomorrow in class we can take our oaths quickly and efficiently. Also, Glenn (roe on the contributor list) will be tomorrow's scribe.