Tag Archives: oreos

Are They Really Doubly Stuffed? [#MCTM]

I’m preaching the good word of Oreos to the people of Minnesota today (9:25 in Harborside 203, if you’re in Duluth this morning).

Here is a link to the definitive collection of Oreo-related posts in the blogosphere. If you have others, send them my way and I’ll add them to the collection.

A couple of evaluations. A few called for more close ties to a classroom task. I get that, and I think it is reasonable for teachers to use this context and adapt for their own instruction (see reference above to my proposed licensure exam).

The comprehensive Oreo database

Here, representing many hours of data collection, including several notebook-equipped excursions to Cub Foods, I present to you the Comprehensive Oreo Database.

I would like to replace the present system initial licensure exams in secondary mathematics teaching with a single task: Design a mathematics lesson around some or all of this information, including answer key for all tasks.

Until this happens (at which point the information below will be embargoed for test-security purposes), I share it with you.

Oreo type Serving size (in cookies) Calories per serving Fat grams per serving Mass per serving Notes Regular 3 160 7 34 Berry burst ice cream 2 150 7 30 Candy corn 2 150 7 29 Chocolate 2 150 7 30 Double chocolate fudge creme 3 180 9 36 One choc. wafer & one serving choc. stuf, coated in fudge Double Stuf 2 140 7 29 Double Stuf Heads or Tails 2 140 7 29 Football 2 120 5 26 These are shaped like a football Golden 3 160 7 34 Fudge creme 3 180 9 35 One choc. wafer & one serving van. stuf, coated in fudge Golden chocolate 3 170 7 34 Golden Double Stuf 2 150 7 30 Halloween 2 140 7 29 Mega Stuf 2 180 9 36 Reduced-fat 3 150 4.5 34 Spring 2 150 7 29 Triple-double 1 100 4.5 21 Triple-double Neapolitan 1 100 4.5 21

Systems of linear equations

The way I see it, there are two types of systems of linear equations problems:

1. Those in which each equation represents a function relationship between two dynamic variables. We will call these racing problems, and
2. Those in which each equation represents partial information about two or more static relationships and we seek to infer information from the system. We will call these unknown value problems.

Racing problems are pretty easy to cook up and to make plausible. One person gets a head start, but runs more slowly. There is a greater start up cost for service A, but the unit rate is less than for service B. Et cetera. We make some simplifying assumptions (e.g. that rates are maintained throughout the race), but with a bit of finesse it’s not too challenging to make these seem reasonable, and thus to avoid the dreaded pseudocontext.

But unknown value problems are a different beast. Here are two classics of the form:

Boat in the river. Kerry’s motorboat takes 3 hours to make a downstream trip with a 3-mph current. The return trip against the same current takes 5 hours. Find the speed of the boat in still water. From Bittinger, et al., College Algebra: Graphs and Models.

Juice blends. The Juice Company offers three kinds of smoothies: Midnight Mango, Tropical Torrent, and Pineapple Power. Each smoothie contains the amounts of juices shown in the table. On a particular day, the Juice Company used 820 ounces of mango juice, 690 ounces of pineapple juice, and 450 ounces of orange juice. How many kinds of smoothies of each kind were sold that day? [Table omitted-you get the point] From Stewart, et al., College Algebra, Concepts and Contexts.

Variations involve canoes and known distances instead of known current speeds, or (worst of all) known differences in canoeing speeds, but unknown canoeing speeds. They also include varieties of gasoline sold, together with known totals, but unknown breakdowns. These are all completely phony, and what are we doing measuring boating speeds in miles per hour, anyway?

It took many trips through the land of College Algebra before I could put my finger on the difference between racing problems and unknown value problems. Part of the difficulty is that unknown value problems often masquerade as racing problems, as in the Boat in the River problem.

[Note: This confusion between dynamic racing problems and static unknown value problems may well be what I find so compelling about Dan Meyer's escalator problem, and what several of my colleagues find so baffling and uninteresting about it. Also, these things may be due to other factors.]

When I wrote my Oreo manifesto, I was on the verge of a breakthrough on these matters. And now I offer the results of this breakthrough to you. The key question for me was this: What are some scenarios in which we really do have information about sums of parts, without knowing the values of the parts?

I have two such scenarios, each of which breeds many real-world problems.

Scenario 1: Nutrition labels

These are the Oreo problems. If we accept—as Chris Lusto has demonstrated decisively—that Double Stuf Oreos are in fact doubly stuffed, then we can use nutrition labels to answer questions such as, Are there more calories in the stuf of a regular Oreo, or in a wafer? What about fat? Nutrition labels give us information about the calorie (or fat) content of the whole cookie; we need to infer the calorie (or fat) content of the constituent parts.

Having mastered that technique, we can move on to Ritz Crackerfuls. The Big Stuff Crackerful has “75% more stuff” in the middle. Again, data from the nutrition label allows us to use a system of equations to infer the caloric content of the crackers and of the cheesy stuff.

Then it’s on to milk. One percent milk has 100 calories per cup. Two percent milk has 120 calories per cup. (These are approximations, of course). So how many calories should be in a cup of skim milk? How many calories should be in a cup of pure milk fat (the answer is surprisingly large)? And what percent is whole milk, anyway, given that it has 150 calories per cup (this one is surprisingly small if you don’t know the answer already)?

Scenario 2: Prices of mixtures

E85 is 85% ethanol, 15% gasoline and is cheaper than regular gasoline in the Midwest. Regular gasoline, though, has ethanol in it too-typically 10%. We should be able to use a system of equations to compute the underlying prices of pure ethanol and of pure gasoline (again, I get that there are simplifications involved here), and then to predict the price of gasoline with 20% ethanol, which will be required in Minnesota sometime in 2013.

A simpler version of this comes from my trip east this past summer. In rural North Carolina, I found a gas station that proudly announced that one of its two pumps dispensed “Ethanol Free” gasoline, while the other warned that its gasoline contained 10% ethanol. The former was more expensive (and does not exist in Minnesota, which is what made the sign remarkable to me).

At my local butcher shop, 90% lean ground beef costs \$3.89 per pound, while 85% lean ground beef costs \$3.69 per pound. What does this say about the underlying per-pound price of beef fat? How about of pure lean beef?

It occurred to me for the first time last night that I could apply the pricing techniques to Oreos. That is, I began to wonder whether the Triple-Double Oreo is fairly priced. We should be able to infer the price of a serving of stuf, and the price of a wafer, then calculate the expected cost of a bag of Triple Double Oreos. My experience is that all bags of Oreos are priced the same, regardless of contents. So is it fair? I don’t know. But I’m gonna find out.

Conclusion

So there you have it. Two scenarios, each with multiple examples, in which to situate your unknown value systems of equations problems. You no longer have an excuse for assigning the Boat in the River problem.

I’m watching you.

I’ll know if you do.

Postscript

A further distinction between racing problems and unknown value problems is that racing problems are usually best modeled with slope-intercept form while unknown value problems are usually best modeled with standard form.

It can be hard to see the Oreo problem as a function relationship (the number of calories in a wafer depends on the number of calories in a unit of stuf? Not really.)

Similarly, it seems weird to describe the running of a race in standard form. $y=5x+20$ can describe someone who got a 20 meter head start, and who runs 5 meters per second. But to rewrite this as $-5x+y=20$ obscures these facts. Why should the sum of the distance and the opposite of 5 times the elapsed time be constant at 20?

Nutrition information for Candy Corn Oreos

You should know that Candy Corn Oreos exist, and that one serving consists of 2 cookies which collectively weigh 29 grams, contain 150 calories and 7 grams of fat.

You should know further that one serving of candy corn consists of 19 pieces which collectively weigh 39 grams, contain 140 calories and 0 grams of fat.

You do the math.

Diagrams, week 1

It is officially a thing now to post a photograph from our classrooms every day of the school year. I can’t keep up with that.

But I have written about the importance of differentiating between diagrams and decorations. And I have a swanky new iPad (Thanks TED-Ed!) So I’ll aim to get a diagram from my teaching up here each week. Some will be mine. Some will be my students’. Some may represent thinking transparently. Others may be more challenging to interpret.

All will be examples of representing mathematical thinking with pictures.

Today we worked on the Oreo problem in College Algebra. Specifically, given information freely available on the Nutrition Facts labels on regular and Double Stuf Oreos, and given the assumption that Double Stuf Oreos are in fact doubly stuffed, we asked:

Where are there more calories in an Oreo? In the wafers or in the stuf? And how many calories are in each?

Along the way, I drew this diagram to represent a student’s words. The A, B, C and D were his letters, as were what they referred to. I just drew the picture for all to see.