Introduction to R Programming

Equation: y_i = a + bx_i + e_i

(Check assumption after testing)

Assumptions of the Simple Linear Regression Model:

1. linear relationship between x and the expected value of y
2. independence between any given (x_i, y_i) pair and any given (x_j, yj) pair
3. error terms e is normally distributed
4. error terms for all values of x has equal variance

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Interpretation:

We estimate that for every 1 unit increase in the age, the expected lung capacity will increase by 0.54485.

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More Linear Regression Output

• Predicted values for observed data

                    predict(mod) 

• Residuals 

                    resid(mod)

          Residuals are actual error terms from the estimated line. residuals = yi - estimated yi

Diagnostic plots:

• Residuals vs. Fitted
• Normal Q-Q
• Scale-Location
• Residuals vs. Leverage