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Material Type: Assignment; Class: Linear Models; Subject: Mathematics; University: University of Utah; Term: Fall 2004;
Typology: Assignments
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Homework 1 Consider the following hypothetical data; it is regarding a particular bird species:^1
Wing length (cm) Age (days) 1.5 4. 2.2 5. 3.1 8. 3.2 9. 3.2 10. 3.9 11. 4.1 12. 4.7 14. 5.2 16.
Use simple linear regression to predict the age of a newly-caught bird whose wing is 4.0 centimeter long. Assuming normal errors, test the hypothesis (95%) that wing length and age are linearly related.
Solution. Let the ages be denoted by y 1 ,... , y 9 , and the wing-lengths by x 1 ,... , x 9. You should compute:
x¯ ≈ 3. 46 sx ≈ 1. 17 y¯ ≈ 9. 89 sy ≈ 3. 92 Corr(x, y) ≈ 0 .99.
Now recall that the regression line is described by
y = ¯y + β̂ (x − ¯x),
where β̂ = Corr(x, y) sy sx
So the regression line is (approximately) given by
y = 9.89 + 3.3(x − 3 .46).
Plug in x = 4 to obtain the regression estimate:
y = 9.89 + 3.3(4 − 3 .46) ≈ 11. 21.
This answers the first question. To answer the second question recall that
β̂ ∼ N
β,
σ^2 ns^2 X
(^1) Borrowed from http://math.hws.edu/javamath/ryan/Regression.html 1
2
Here, n = 9. Pretend that this is large enough. [This is not so good, and will be addressed later on.] Then, one would expect that σ^2 = Var(y) ≈ s^2 y ≈ 3. 922 ≈ 15. 37. Also, s^2 x ≈ 1. 172 ≈ 1 .37. So, we would
expect β̂ to have approximately a normal distribution with mean β and variance
Under H 0 , β̂ ≈ N (0, 1 .25).
Therefore, the sample’s β̂ = 9.89 gives us a P-value of ≈ 0 .0. I.e., good reason to believe that H 0 is false; i.e., β 6 = 0; i.e., there is some linear relation between x and y.