My latest contribution to the New York Times Learning Network is a math lesson built around investigating the indicators analysts use to classify and predict economic recovery.
http://goo.gl/m2F0J
By collecting and analyzing data presented in Times infographics and other official sources, students can analyze the various economic indicators to assess the current condition of the U.S. economy.
By comparing and contrasting the various indicators, and connecting these abstract measures with their own personal experiences, students begin to build understanding of the complex task of quantifying economic performance.
Click here to see more in Teaching.
www.MrHonner.com
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This is an interesting article about variations on the pay-what-you-wish pricing model that has gained some attention in the last few years.
http://goo.gl/7YLu
The band Radiohead famously offered their album “In Rainbows” on their website and asked fans to pay whatever they wanted for the download. The actual sales numbers are well-guarded, but it appears to have been a success.
The above article details how an amusement park merged the pay-what-you-want approach with a half-goes-to-charity approach (telling the customer that half of the purchase price is donated to charity). The product in question was a picture of the customer riding a roller coaster. Let’s abbreviate with PWYW (Pay What You Wish), HGTC (Half Goes to Charity), and PWWTY (pay-what-we-tell-you):
| |
Percent Sales |
Average Sale Price |
| PWWTY |
.5% |
$12.95 |
| PWWTY & HGTC |
.57% |
$12.95 |
| PWYW |
8.4% |
$0.92 |
| PWYW & HGTC |
4.5% |
$5.33 |
When given the opportunity to pay whatever they wanted, participation increased dramatically, but revenue was still low–only 92 cents per person. But when combined with the half-goes-to-charity approach, participation was much higher and the price paid was significantly higher. Even after taking out the half for charity, revenue was still up by a factor of three!
This is a very interesting approach to pricing, and there are some cool psychological and sociological principles at work here. And it’s another set of factors to consider when that salesperson is working on you.
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This is a nice takedown of some spurious economic analysis, courtesy of Freakonomics:
http://www.freakonomics.com/2011/03/30/how-to-spot-advocacy-science-john-taylor-edition/
Looking at the graph at the right, it’s hard not notice the negative correlation between the two given variables, and the economist in question uses that correlation to bolster his policy argument.
The graph looks a lot different, however, when you look at all the available data, not just the data between today and the arbitrarily chosen cut-off of 1990. But that chart doesn’t support the argument as decisively.
As the author suggests, “Be wary of economists wielding short samples.”
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This is an interesting article from NPR about how much it costs to make a hit pop song.
http://goo.gl/Go4mG
Using a Rhianna song as an example, this article breaks down the approximate costs for songwriters, producers, engineering, and marketing.
Before reading the article, take a guess as to how much of the money spent on making a “hit” song goes to creative artists: you’ll almost certainly be surprised.
Click here to see more in Application.
www.MrHonner.com
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My latest contribution to the New York Times Learning Network is a math lesson built around gathering, representing, and analyzing economic indicator data.
http://goo.gl/Rcc50
By getting data on Real G.D.P., personal income, corporate profits, and unemployment from official sources like the Bureau of Economic Analysis and the U.S. Department of Labor, students explore positive and negative correlations between the various economic indicators.
In addition, students can explore the relationships between graphs of quantities and their rates of change by creating and comparing graphs of percent change.
Click here to see more in Teaching.
www.MrHonner.com
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My latest contribution to the New York Times Learning Network is a math lesson built around investigating the indicators analysts use to classify and predict economic recovery.
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