Concept explainers
(a)
To explain why a linear model is appropriate for describing the relationship between temperature and distance to the nearest fish.
(a)
Explanation of Solution
A linear model is appropriate for describing the relationship between temperature and distance to the nearest fish because the pattern in the
(b)
To write an equation of the least square regression line.
(b)
Answer to Problem AP3.33CPT
Explanation of Solution
It is given that researchers want to study about is the temperature of the water discharged by the plants causes harm to the fishes of the water body or not. Thus, a scatterplot was been made on the temperature and distance to the nearest fish. Then, computer output from a least square
From that we know that, the coefficients for the regression line is listed under the heading "Coef" and the constant is the intercept. Also, temperature is the slope. Thus, now we can calculate the regression line as:
Where
(c)
To interpret the slop of regression line.
(c)
Answer to Problem AP3.33CPT
On average, the distance to the nearest fish increases by
Explanation of Solution
It is given that researchers want to study about is the temperature of the water discharged by the plants causes harm to the fishes of the water body or not. Thus, a scatterplot was been made on the temperature and distance to the nearest fish. Then, computer output from a least square regression analysis on these data and residual plot information is given in the question.
From part (b), we know that the regression line is as follows:
The slope as we know, is coefficient of
Thus, we have,
So, we can interpret that on average, the distance to the nearest fish increases by
(d)
To compute the residual for the point
(d)
Answer to Problem AP3.33CPT
The predicted distance is
The residual is
Explanation of Solution
It is given that the point is
Now, we know from part (b), that the regression line is as follows:
Let us now find out the predicted value, which can be calculated by evaluating the least square regression line at
Now, as we know residual is the difference between the actual
Thus, we conclude that, the predicted distance is
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