1.) Describe the association between "number of missed classes" and "exam score." -- this is on the paper we had with our "notes examples" about cucumbers and ankle range of motion. Or, here's the context:
2.) Textbook Page 189 - 193 : 11a, 13abc, for 13's context also interpret the yintercept, 35cef
- For 13c this is called a "residual"-- for this homework just worry about the math
- For 35cef you'll need to find the equation using your graphing calculator (x = fat, y = calories)
- Period H: Here's some help with interpreting the y-intercepts since we didn't get to it in class:
- Remember, the y intercept occurs whenever the x = 0
- We just want to take this idea that "x = 0" and turn it into the given context
- For example--back to ankle range of motion and balance scores...
- The yint = -1.993, so "when x = 0, y = -1.993."
- In context, "when ankle range of motion (x) = 0, balance score (y) = -1.993"
- Sometimes the y-intercept has an unrealistic interpretation--if so, we have to comment on that; in this case, the y-intercept is unrealistic because a balance score cannot be negative!
- Read the full interpretation in the image below...
- Here's the answer to the "describe the association" question:
- "Based on the scatterplot the association between number of missed classes and exam score is roughly linear, negative, and pretty strong with a correlation of -0.79; generally, as the number of missed classes increases, exam score decreases."
- Check the back of the book for the textbook stuff....
- However, any interpretations of slope/yint MUST start with "THE MODEL PREDICTS," which is not done in the back of the book.
- Here's the answer to "interpret y intercept" (question I added) for the context in 13:
- "The model predicts that if a house has a size of 0 square feet its predicted price is about 47.82 thousand dollars. This is unrealistic because a house would not exist if it were 0 square feet."
We will have a chapter 7 quiz to start class on Tuesday!
- Open Ended Section:
- Describe an association
- Maybe an open ended like today's stamp (identify mistakes with statements about r, hypothesize about a lurking variable)
- Vocab Section:
- Scatterplot
- Explanatory (Variable)
- Response (Variable)
- Lurking Variable
- Describe an association (what do we describe?)
- Correlation
- Also be sure to know the "facts about correlation"
- Positive Association
- Negative Association
- Y-Hat
If you were out today we discussed how to interpret slope and y-intercept--there are some notes to get before this, but here are the end products for our interpretations:
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