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This tag is associated with 2 posts

Population Growth Estimate Gets Spooky


Here’s a statement of mathematical certainty…”On October 31, the world population will reach 7 billion people”. Or will it? The Wall Street Journal article, “How Do You Get to 7 Billion People” discusses this topic and the issues associated with population accuracy.

Extra Credit Assignment (worth 5 points on your next learning packet – comments due by the date and time your packets are due) follow the directions below carefully. If directions are not followed exactly, points will not be earned.

ARITHMETIC STUDENTS (MAT082) – Respond to the following in the comments area below:

  1. Your first name, last initial, and the class you are in (082)
  2. The linked article talks about some of the issues with accurately counting people. Name one of these issues and why it makes accurate counting difficult.
  3. What does the article say about why accurate counting is important? Why do we care? List at least one reason and why it is important.

INTRODUCTORY ALGEBRA STUDENTS (MAT092) – Respond to the following in the comments area below:

  1. Your first name, last initial, and the class you are in (092)
  2. Using the listed data for the US Population in 1950, 2010, 2050, make a reasonable estimate for our population in 2100. Explain your process carefully.
  3. How does your estimate compare to what the article says will be the US population in 2100? What might account for the difference?

INTERMEDIATE ALGEBRA STUDENTS (MAT122 or 121) – Respond to the following in the comments area below:

  1. Your first name, last initial, and the class you are in (122 or 121)
  2. Use LINEAR regression to write an equation for the population growth of China from 1950 to 2010. Then, use EXPONENTIAL regression to do the same thing. Include your equations here and explain your processes.
  3. Use your equations above to compute the population of China in 2050 and include those numbers and calculations here. Which of your models is more accurate to the 2050 prediction?
  4. What might happen to explain the predicted drop in population from 2050 to 2100? Would either model have anticipated this?

Marathons and Medians – Graphics


Saw an article in the Wall Street Journal over the weekend about marathon runners and times. I love the graphics they use and the charts and tables and all. Did some poking around and couldn’t find their graphic online to look for copyright info and a place to request permissions to use their images. But, I did track down the data source (listed at the bottom of the article) as a website called Running USA and a place on their website where statistics and reports about the state of marathon races in the U.S. are posted. From that website, I noted data for Median Marathon Times and for Number of Finishers. The graphs and those data are listed below.

Ways to use these graphics include:

  • Ask students to identify the number of runners that finished a marathon in a given year.
  • Ask students the median time of marathons for males or females in a given year.
  • Ask students to generate a linear regression model for the median times and for the number of finishers then use those models for predictions.
  • Ask the students reasons why the median times are staying the same even though the number of runners in increasing.
  • And many more!

The data are public and my graphs are Creative Commons so use any way you want according to the licensing information below the images.

Creative Commons License
Marathons and Medians by Donna Gaudet is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.

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