**Chapter 14 Notes:
Inference for the Regression Model:**

Step 1: Make a scatterplot

Step 2: Calculate
the LSRL

Step 3: Identify
outliers and influential points

Step 4: Calculate
the correlation (r value)

** Assumptions for Regression Inference:**

1. The y responses vary according to a
normal distribution.

2. The y responses are independent of each
other.

3. The true relationship is linear.

4. The standard deviation s about the true regression line is constant.

The true regression line is
written in the form: _{} where a is the true x-intercept and b is the true slope.

Since s is unknown, we use s to estimate the value of s.

_{}

Note: (n – 2) is the degrees
of freedom for the regression model.

A level C
confidence interval for the slope b of the true regression line is _{}.

_{}

To test whether or not there
is a correlation between two quantitative variables,
consider the slope of the regression line.
If there is no correlation, the slope would be zero.

H_{0}: b = 0 _{}

To test this hypothesis,
compute the *t* statistic and P-value.