In that first column we have that estimate for each coefficient. To model a line, we use the equation Y = a + bX, and the goal of the regression analysis is to estimate the a and the b. Remember that two coefficients get estimated from a basic linear model: The intercept and the slope. # F-statistic: 10.71 on 1 and 29 DF, p-value: 0.002758īeneath ‘Call’ and where it shows us what our model looks like, we can see the distribution of the residuals or unexplained variance in our model: the min and max, the 1st and 3rd quartiles, and the median.īut below that we have a table that gets a bit more interesting… # Residual standard error: 2.728 on 29 degrees of freedom
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