Wednesday and Thursday HW

Tonight, please complete the following in your textbook:

Page 190-196: 15b, 36ab, 41b, 47f

• Period A: notice this book assignment is shortened from class!
• All of the answers are provided below so you can check (using the same type of wording I taught you in class)
• 15b, 41b, and 47f all ask you to interpret R^2--use the writing template provided today in class (or below)!
• Here are the homework answers so you can check:
• 15b.) About 92.4% of the variability in nicotine content (mg) in cigarettes can be explained by variability in the amount of tars (mg). Other factors may include the type of cigarette.
• 36a.) A linear model is appropriate because the scatterplot appears roughly linear and both variables, fat (g) and # of calories, are quantitative.
• 36b.) There is a strong association between amount of fat and number of calories in chicken sandwiches because r = 0.947 (which is close to 1).
• 41b.) About 33.4% of the changes in mean annual temperature (degree Celsius) can be explained by changes in the mean annual CO2 concentration in the atmosphere (ppm). Other factors may include
• 47f.) About 43% of the variability in annual mortality rate (deaths per 100,000) for males in England and Wales can be explained by changes in calcium concentration (water hardness), measured in parts per million (ppm).

• *Notice that when I wrote my context I did not simply copy the variable names off of the scatterplot--read the context and be more thorough than what's provided on the graph!

• I'm starting to second guess needing the "other factors" part for the AP exam when interpreting R^2...notice I left this off. I am going to reach out to some other Stat teachers and try to find out if we need this with our interpretation.

Here's what we covered today in class:

• Stamp problem = practice with reading computer outputs
• Homework questions?
• Next we intepreted the slope and y-intercept for the computer output we worked with yesterday in class (# of passenger seats vs. operating cost per hour) so that we would have one more example of these interpretations in our notes
• Then we focused on the meaning of R^2, or the Coefficient of Determination...
• We watched the AP Stat Guy video about R^2 in class (watch it)! (unit 2, video #9)
• We also discussed how to interpret R^2--here's a writing template you can use for your homework/quizzes/tests/etc
• "__R^2__% of the variation in __(response variable)__ can be explained by variation in __(explanatory variable)__."

• Here's an example based on the computer output:
• "Approximately 57% of the variation in operating cost per hour can be explained by variation in the number of passenger seats. Other factors may include the weight of the plane or the length of the trip."

Tomorrow in class we'll wrap up any questions we have about slope, intercept, and R^2 and we'll start to explore residuals! See you there! On Friday we'll start class with a (15 minute) quiz--all writing/interpreting!

And if you're feeling ambitious here's tomorrow night's homework--all practice to get ready for our quiz Friday! (this assignment is actually just a different version of the quiz)