1. AP Statistics
Chapter 14
Section 1

2. The slope of the true regression line.
The slope of the least squares regression line used to estimate
The true intercept of the real regression line.
The intercept of the least squares regression line – used as an unbiased estimator of

3. Linear Regression Inference
Make a scatterplot of the data.
Find the least squares regression line that fits the data. Place on graph with equation.
Look for outliers or influential observations.
Look at residuals to determine the fit of the prediction line.
Look at r and r2.
Write null and alternative hypotheses.
Check assumptions
Test statistic
P-value
Conclusion

4. How well do golfer’s scores in the first round of a tournament predict their scores in the second round?
Golfer 1 2 3 4 5 6 7 8 9 10 11 12
Round 1 89 90 87 95 86 81
102
105 83 88 91 79
Round 2 94 85 76
107 80
100 90 80
Round 1

5. Round 2 vs Round 1
Residuals
Based on the residual graph and the range of
the residuals the use of this model for inference
would be appropriate. The correlation
coefficient and coefficient of determination are
moderately strong as well.

6. Linear Regression Test
Assumptions:
For any fixed value of x, the response y varies according to a normal distribution. Repeated responses y are independent of each other.
The mean response has a straight-line relationship with x.
The slope and the intercept are unknown parameters
The standard deviation of y is the same for all values.

7. Given that the slope is 0 the observed result will occur approx
Given that the slope is 0 the observed result will occur approx. 1 out of every 100 times just by chance. Therefore this evidence rejects that the slope is 0.

8. We are 95% confident that for every unit of change in the first round of golf the score of the second round will change between -4 and 5 points.