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Holiday Math Activity: Roasting a Thanksgiving Turkey November 1, 2015

Posted by Edward Deleon in : algebra, math, media , add a comment

Roasting a Turkey

Now that Thanksgiving is approaching, it’s time to start preparing for cooking a turkey. The USDA recommends cooking an unstuffed turkey or a stuffed turkey, according to these guidelines. These guidelines provide an excellent opportunity to explore graphs and equations of linear functions.

 

Unstuffed
4 to 8 pounds (breast) 1½ to 3¼ hours
8 to 12 pounds 2¾ to 3 hours
12 to 14 pounds 3 to 3¾ hours
14 to 18 pounds 3¾ to 4¼ hours
18 to 20 pounds 4¼ to 4½ hours
20 to 24 pounds 4½ to 5 hours

 

Stuffed
4 to 6 pounds (breast) Not usually applicable
6 to 8 pounds (breast) 2½ to 3½ hours
8 to 12 pounds 3 to 3½ hours
12 to 14 pounds 3½ to 4 hours
14 to 18 pounds 4 to 4¼ hours
18 to 20 pounds 4¼ to 4¾ hours
20 to 24 pounds 4¾ to 5¼ hours

 

Activity

For this activity, students can use a graphing calculator or software. Show students a prepared coordinate grid like the one shown here. They can use it to sketch out data and graphs and use the graphing calculator to test different scenarios.

Turkeygraphs1

Here is a link to a jpg version of this file. Right-click to download it.

Graph1

Have them graph the data from the table for the unstuffed turkey, like the one shown here.

Turkeygraphs2

Here is the downloadable version of this graph.

Graph2

Ask the following questions:

  1. Is there a linear function that could approximate the weight-vs.-baking time?
  2. Use your graphing calculator to find a possible function. What is the equation of the function that you found?
  3. Test the function against the data table. Does it give accurate results?
  4. Did you need to revise your function? What is the new equation?

Once students have worked with the data for the unstuffed turkey, have them work with the data for the stuffed turkey. The graph is shown here.
Turkeygraphs3
Here is the downloadable version of this graph.

Graph3

Repeat the previous set of questions with this graph.

Finally, combine both sets of data and include the functions. The combined data graphs are shown here.
Turkeygraphs4
Graph4

Math in the News: Jurassic World October 3, 2015

Posted by Edward Deleon in : Uncategorized , add a comment

 

In this issue of Math in the News see how Jurassic World has set box office records.

Click here to see it.

 

Math in the News: The Decreasing Price of Gasoline December 7, 2014

Posted by Edward Deleon in : algebra, graphing calculators, math, media , add a comment

Slide01.jpg

In the current issue of Math in the News we look at data around the price of gasoline and oil production. We analyze graphs and look for functional relationships among the data sets. This is a great opportunity to bring a timely, real-world connection into your classroom.
This slide show includes an embedded GoogleDoc with all the data, which you can then copy and paste into a spreadsheet or graphing calculator to create your own graphs.

Math in the News: Issue 89 January 31, 2014

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In our latest issue of Math in the News we look at Super Bowl statistics. #MathChat http://ow.ly/t8bOj

Math in the News: Issue 89 January 31, 2014

Posted by Edward Deleon in : algebra, math, media , add a comment

In our latest issue of Math in the News we look at Super Bowl statistics. #MathChat http://ow.ly/t8bOj

Math in the News: Issue 85 January 3, 2014

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In this issue of Math in the News we look at box office data from 2013. We look for patterns in the data and analyze the data using different data displays, including bar graphs, line graphs, scatterplot, and tables. This provides an excellent opportunity for data analysis.

Math in the News: Issue 85 January 3, 2014

Posted by Edward Deleon in : algebra, math, media , add a comment

In this issue of Math in the News we look at box office data from 2013. We look for patterns in the data and analyze the data using different data displays, including bar graphs, line graphs, scatterplot, and tables. This provides an excellent opportunity for data analysis.

The Rise and Fall of Blackberry October 1, 2013

Posted by Edward Deleon in : algebra, math, media , add a comment

Image

In our current issue of Math in the News, we look at the financial woes of Blackberry. Here was a company that at one time was the preeminent supplier of phones and other handheld devices. But in what seems like the blink of an eye, Blackberry has been reduced to a bit player, and soon won’t even be a publicly held company.

The Blackberry story is a textbook case of a company whose product isn’t hardware, but innovation. For a long time, Blackberry provided innovative solutions to cell phones with email capabilities. Their mini-keyboards became the hallmark of their clever designs.

But along came Apple and Android and the cell phone was transformed into the Smart Phone. Rather than merely a phone with email capability, the iPhone, and later Android phones, turned Blackberry devices into quaint relics. From 2008 to 2012, Smart Phones outpaced older-style Blackberry devices. Blackberry responded with similarly styled Smart Phones, but it was too late.

The evidence of Blackberry’s decline is obvious by analyzing its financial statements. In two issues of Math in the News we analyze Blackberry’s finances. The analysis confirms that Blackberry just couldn’t sell its own version of Smart Phones.

Financial analysis of publicly traded companies should not just be the domain of stockbrokers and Wall St. people. There is a lot of good data that can be mined and used in a math class. We will continue to publish more analyses of this type, in order to encourage math teachers too analyze real-world data. Once you do, you’ll be astounded at the wealth of material to work with.

Here we reproduce the current issue of Math in the News.

Diana Nyad’s Epic Swim September 4, 2013

Posted by Edward Deleon in : algebra, math, media , add a comment

Image

In our current issue of Math in the News we look at Diana Nyad’s remarkable swim from Havana to Key West, Florida. We analyze the time and distance covered and use that as an opportunity to explore Average Speed.

Average Speed results in a linear function, and is useful for describing overall motion. But it’s not as useful for describing motion at specific locations and times. So, we analyze the data generated from Nyad’s swim relative to the Average Speed. This provides an excellent opportunity to see how disparate data points are smoothed out by the Average Speed function.

We reproduce the Math in the News issue as a SlideShare Presentation here:

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