CORRECT ANSWERS
Question:
1. Linear Regression
Answer:
a way to model the relationship between 2 quantitative variables with a line
Question:
2. Y-intercept & slope
Answer:
the 2 parameters of a linear model
Question:
3. mean & standard deviation
Answer:
the 2 parameters of a normal model
Question:
4. b0
Answer:
y-intercept
Question:
5. b1
Answer:
slope
Question:
6. response variable
Answer:
y axis
Question:
7. explanatory variable
Answer:
x axis
Question:
8. y
Answer:
the actual or observed response value
Question:
9. Y hat
, Answer:
the predicted or fitted value
Question:
10. the linear model
Answer:
y hat = b0+b1(x)
Question:
11. risidual
Answer:
observed value - predicted value=
Question:
12. extrapolation
Answer:
to make predictions outside the range of data observed
Question:
13. outliers
Answer:
points that don't follow the overall pattern of the rest of the data; don't always have large residuals
Question:
14. high leverage
Answer:
points outlying in their x values; high or low
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15. influential point
Answer:
when a point changes the least squares line
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16. simulation
Answer:
repeating some random phenomenon many times and observing the outcome
Question:
17. least square method
Answer:
most common method for finding a best fitting line; minimizes the sum of the squared residuals
Question:
18. slope formula