Confidence Intervals (CI) for Dependent Variable Prediction

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In all likelihood, your model will not perfectly predict Y.
The SEE can be extended to determine the confidence interval for a predicted Y value. A common CI to test for a predicted value is 95%.
Your regression parameters, the y-intercept (b0) and slope coefficient (b1) will need to be tested for significance before you can generate a confidence interval around your model’s project Y value around an expected X value.