Posts Tagged ‘mathematical modeling’

Making Box Plots on Ti-84

August 15, 2017

Quick graphs on the Ti-84 is a good way to  see how data is distributed.  The attached document gives step by step instructions along with an example to practice.

Making a Box Plot on the TI 84

VC Firms Use Big Data to Seek Out the Next Big Thing

April 25, 2017

Venture Capital firms, that is, firms that invest in funding start-ups, early stage  companies, and companies with good growth potential, are always on the hunt for the next great opportunity.  The article below talks about the trend away from people who are expert in spotting such opportunities, and towards computer based analytics which is believed to be faster and better at finding the “next big thing.”

Venture-Capital Firms Use Big Data to Seek Out the Next Big Thing – WSJ

 

“At the current rate…” and other assumptions

March 30, 2017

In order to make any predictions in any area of study, one must make assumptions about the data, and what is likely to affect it going forward.  That is why statistical studies often make use of such statements as:

“At the current rate…”

“If things continue as in the past…”

“Based on what we know now…”

“It is reasonable to assume…”

“If history is a guide…”

“If things don’t change…”

But things do change, and that is what makes predicting the future so difficult, and so vulnerable to known and unknown biases.  While these caveats are unavoidable, and need to be stated, they require the consumer of the statistics to have a reasonable amount of skepticism and a large amount knowledge.

A quote in a The Great Race by Levi Tillemann states that “The available supply of gasoline, as is well know, is quite limited and it behooves the farseeing men of the motor car industry to look for likely substitutes.”  This quote is attributed to Thomas J. Fay, in 1905, in a magazine call Horseless Age.

Math Being Used by Cancer Researchers

July 4, 2013

The following article from the NY Times discusses how mathematical models are being used to understand how different cancer drug therapies can be used for optimal results.

Math in cancer research