My Favorite: Linear Regression & Movies

Week 2 of the #MTBoS challenge: "My Favorite".

There are many lessons and activities that I have that could qualify as "My Favorite", but since I haven't blogged about this one yet, I'll go with it.

For the past couple of years, I used an activity I found on Yummy Math to help apply linear regression to a real world context.  I modify the activity just a bit by changing some of the movies to some of my favorites.  (If you haven't check out Yummy Math yet, I'd recommend it.  A lot of the site is free, but I'd recommend paying the $20 per year for full access.  The best thing about Yummy Math is that they're always updating their activities.)

Using Desmos, it's very quick and easy to create regression equations.  Students are asked to find some of the data from their own favorite movies, which completely draws them into the activity.

There is a lot of opportunity for rich discussion in the activity.  Some examples of really great discussions I've had w/ this activity:

• Why are some movies way above or below the line of best fit?  What would cause that sort of behavior?
• How does inflation / release dates play a role in this data?
• Why do Disney animated movies tend to be below the line of best fit?
• Why are sequels typically below the line of best fit?
• Are most of the top-grossing films of all time (Titantic, Avatar, and now Star War 7) above the line of best fit?
• When looking at a series of films (ex: Fast & the Furious), why do some fall above the line while others fall below?

Lastly, I love the activity because it leaves a bit of a cliffhanger.  Each year I do this, I wait and see what is the #1 movie in America during the past weekend and include that as part of my data set.  This past year, it was Hotel Transylvania 2.  At the end of the activity, I have students write down their prediction for the total gross amount for that movie.  Of course, there is no right answer at the time since the movie is still in theaters.  So we wait and occasionally check on it throughout the semester.  When the dust settles, we look back and see which student was closest to correct and award a prize.  

Title	Opening Gross ($ in millions)	Total Gross ($ in millions)	Opening Date
The Avengers	207.438708	623.279547	5/4/12
The Hunger Games: Catching Fire	158.074286	424.668047	11/22/13
Harry Potter & the Deathly Hallows Part 2	169.189427	381.011219	7/15/11
Jurassic World	208.806270	650.493056	6/12/15
The Sandlot	4.918712	32.434006	4/9/93
Toy Story 3	110.307189	415.004880	6/18/10
Dumb & Dumber	16.363442	127.175374	12/16/94
Frozen	67.391326	400.738009	11/22/13
Avengers 2: Age of Ultron	191.271109	458.924272	5/1/15
Major League	8.836265	49.797148	4/7/89
Hotel Transylvania 2	48.464322		9/25/15

One Good Thing

I'm giving semester tests today.  For algebra 2, I allowed students to have one page of paper to be used for a "cheat sheet" to reference during their test.  I collect them from the students when they are finished with the test, mainly so that they don't write things down during the final and then leave and tell their friends what to expect on the test.  (I not naive - I know kids go and talk to their friends about the final, but this way they at least don't have a way to write things down.) 

If you have never done this before, it's really quite interesting what type of cheat sheets students make without any guidance.  (I simply tell them that they can write down whatever they'd like to help them on the final.)  Some students have really great reference sheets, others have very little written down, and yet others have nothing to turn in.

Today, I had one student have something very cool written on their cheat sheet.  We've talked a lot this semester about Growth Mindset.  Here is the cheat sheet:

"YOU CAN DO IT!!" - One good thing from today.

Vikings / Seahawks win probability

Growing up in Minnesota, it's a state law that you must cheer for the local professional sports teams (assuming that you follow sports).  Being the law abiding citizen that I am, I've had to endure numerous heart breaks and losing seasons from my beloved Vikings and Timberwolves.  (I'm also a closet bandwagon Twins fan, but don't know enough about hockey to follow the Wild.)

Today's Vikings loss was as gut-wrenching as any since the 1998 NFC title game.  As I browsed through ESPN tonight, I did happen to stumble onto this crazy Win Probability graph.  I've seen these graphs before; the best ones are when teams have miracle-like wins, such as today's game.

I'm thinking I can use this graph down the road when learning about probability and / or graphs of functions.

For the article that describes some of the swings, click here.  It hurts to be a Vikings fan.