FRACTAL

What is a fractal? Generally "a rough or fragmented geometric shape that can be split into parts, each of which is (at least approximately) a reduced-size copy of the whole,"

We have not yet learned much about fractals but what they can look like, and how to make one.

An example of a fractal can be like this…

An example of one you can make would be as follows...

The blue would be your first box. Then you would make the purple ones which are a reduced size of the first. Then you'd make the green boxes which would be a reduced size of the purple. This can almost go on for infinity, however the size will eventually get to small to be significant or too small to see. We would eventually have to stop because of that factor.

The next scribe is Carmel

STUDY.STUDY.STUDY.

Hey guys we have a test tomorrow so make sure you study, study, study :)

Today we learned that that net worth = assets-liabilities.
Assets is money you have or things of value that you own. There are three kinds of assets:
Liquid Assets: Money you can access easily (cash amounts)
Semi-Liquid Assets: Longer term investments (stocks, mutual funds, or some real estate)
Non-Liquid Assets: Material goods (cars, houses) you have to sell it to make money.
Liabilities is amounts of money that you owe. There are two kinds:
Short Term Debts: Must be paid in the next twelve months.
Long Term Debt: Payments that will take more than a year (mortage).

We also learned today that the Debt/Equity Ratio = (Total Liabilities - Mortage) / Net Worth

You want the outcome of the Debt/Equity Ratio to never be bigger than .5 or 50%. If it is even half a percent higher you will have a hard time finding a bank if you can that will give you a loan. But not is all lost, if it is larger than 50% you may try to get a lower loan, find the money in some bond or somewhere else, take a smaller loan then get another after, or even pay off another debtin order to get that percent 50 or lower.

There a few really good examples of this in the slides Mr.K has put up, so if you feel you need more feel free to also look there.

Wish everyone luck on tomorrows test :) and the next scribe is...Lamael

PoP QuIz

Today we had a surprise quiz. After the surprise we got handed out a worksheet for homework. Everyone make sure you do it because tommorrow Mr.K will be calling people up to show how they did their answers on the board. I will do the first part of the first question with you incase some one is confused how to go about doing them still.



The Stanford-Binet IQ scores of Canadians are normally distributed with a mean of 100 and a standard deviation of 16. According to this test, what is the probability that a randomly selected Canadian will have the following IQs?



a) an IQ less than 100



First you have to find the z-score. Now remember to get the z-score you have to subtract the mean from the number your trying to find the z-score for. Then you divide by the standard deviation. So in this case it would look like...

99-100/16=-0.0625 . Why did i not use a 100 to subtract a 100? This is because the questions asks for a score less than a 100. After finding out the z-score you want to go to shadenorm here you would put in the area you want to find. In our problem here it would look like this...shadenorm(-5,-.0625). Then on your calculator you'd get an area which would be .475082 You then multiply by 100 to make it into a percent which turns out to be 47.5%



the next scribe is Jason

Sorry about the lateness

The first thing we learned yesterday was an easier way to find z scores.

1. Go to stat then edit.

2. Then go to L1 and push in the list of numbers.

3. Go to L2 and at the top push in (L1-mean)/the standard deviation.

4. Now you have your z scores :)



We also learnt about Normal distribution





Above is a picture of normal distribution. Notice how it has a bell shape, this will help you indentify normal distribution in a graph. Most of the data in normal distribution is continuous (has decimal places). There are certain properties of normal distribution which are...
1. 68% of data lies within 1 standard deviation of the mean.
2. 95% of data lies within 2 standadrd deviations of the mean.
3. 99.7% of data lies within 3 standard deviation of the mean.

There are other facts about normal distribution. The area under the curve equals one. The x axis is an asymptote for the curve (the line goes close but never hits zero). Tha graph is symetrical. as well the farther away you go out the less data there is.

Another thing we talked about in class is how to find the mean with the z score. To do this you have to follow the formula (z score * standard devation)+ mean



Next is Daniel