Final answer:
To construct a 95% confidence interval for the slope of the regression model, the standard error of the slope (not provided in the question) and the slope estimate (7.19) are needed, alongside t-distribution critical values. The interpretation of the interval reflects the expected change in weight with each unit increase in snake length. The slope and y-intercept from another example (-0.3031 and 31.93, respectively) describe changes in the percentage of new birds in relation to returning sparrows.
option a is the correct
Step-by-step explanation:
The question refers to the analysis of a regression model to predict the weight of snakes based on their length, as measured in Example 12.2.2. To address part (a) of the question, constructing a 95% confidence interval for the slope (b1) requires statistical output that is typically provided by software which includes the standard error of the slope (SEb1).
Using this, along with the provided estimate of the slope (7.19) and critical values from a t-distribution corresponding to 95% confidence, we calculate the interval. However, the provided information is incomplete as the standard error of the slope is missing. As for part (b), interpreting the confidence interval generally involves stating that we are 95% confident that the true slope of the relationship between snake length and weight falls within the calculated interval, with the understanding that the slope represents the expected increase in weight (in grams) for each additional unit increase in length (in centimeters).
Part (c) of the question: The slope of the regression line is -0.3031, and the y-intercept is 31.93.
The slope represents the change in the percentage of new birds with each additional percentage unit of returning birds. The y-intercept is the expected percentage of new birds when there are no returning birds, which is not a practical scenario since it cannot be 100%, demonstrating the impracticality of extrapolation.