Final answer:
The slope of the regression line represents the rate of change in CEO salary for each unit increase in CEO tenure. The y-intercept is the predicted salary when CEO tenure is zero. The goodness of fit of the regression line can be assessed using the coefficient of determination (R-squared). Residuals indicate the difference between observed and predicted values, with the largest residual representing the point furthest from the regression line. Predicting the number of birds joining a colony would require more information.
Step-by-step explanation:
c. The slope of the regression line tells us the amount of change in the dependent variable (salary) for every unit increase in the independent variable (tenure). The y-intercept represents the predicted value of the dependent variable when the independent variable is equal to zero.
d. The goodness of fit of the regression line can be assessed by looking at the coefficient of determination (R-squared) which measures the proportion of the total variation in the dependent variable that is explained by the independent variable(s). A high R-squared value indicates a good fit.
e. The residual represents the difference between the observed value of the dependent variable and the predicted value from the regression line. The point with the largest residual is the one that deviates the most from the regression line. It may be considered an outlier or influential point depending on its impact on the overall regression model.
f. To predict the number of birds that will join the sparrow hawks colony, you would need more information or data such as the total number of sparrow hawks in the previous year.