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Guidelines:
While you are welcome to work on assignments together and use
resources such as books and websites to help you figure out solutions or
check your work, all assignments turned in should be written by yourself,
including any computer code. Further, your solutions and code should not be
copied from any references or other people's work. In summary, your solutions
should represent your understanding of the assignments.
For computer problems: Please provide
a printout of your input and output. When appropriate, include
comments/explanation and a summary of your answer.
Homework 1 (Due Fri 8/31, in class)
- Read the above guidlines.
- Figure out how to get R
running, either on a personal computer or a university
computer.
- From text: 1.1, 1.3, 1.4
- Using R, determine the equation and plot the simple regression line
for the data x=(1,2,...,15) and y=(y_1,y_2,...,y_15) where y_i is p_i/log(p_i)
and p_i is the ith prime. I.e., p_1 = 2, p_2, = 3, p_3=5, ...
Homework 2 (Due Fri 9/7, in class)
- Get John Verzani's simpleR document (an introduction to R) and go through
the first 4 sections (up to and including the Bivariate Data chapter).
Do and turn in Problems 2.2 and 3.3.
- From text: 2.2.
- From the builtin dataset anscombe in R, plot the data and regression lines
for y1~x1, y2~x2, y3~x3 and y4~x4.
Homework 3 (Due Fri 9/21, in class)
From text: Exercises 2.3, 2.8, 2.9, 2.10.
Homework 4 (Due Fri 10/5, in class)
- Exercise 3.2 from text (note typo: it should say G=46.81, not D=46.81).
- In notation from lecture/text (Sec. 3.4): show P is a projection
onto the image of A along the kernel of the transpose of A.
Homework 5 (Due Fri 10/26, in class)
- From text: Exercises 4.1, 4.6, 4.7 (U(-a,b) is the uniform distribution
on (-a,b)).
Homework 6 (Due Fri 11/2, in class)
- In R, do the ANCOVA in Example 5.8 both without and with interaction.
- Exercises from text: 5.1, 5.5, 5.6., 5.7.
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