MATH 204 - ASSIGNMENT 3
Please Hand in Assignment in the Lecture on Friday 30th March.
For this assignment, all calculations can be done by hand with a calculator. However, you may use SPSS or other
statistics packages.
1. The following data relate to a s
MATH 204 - EXERCISES 2
These exercises are not for assessment
1 Download the SOIL.SAV dataset from the course website at
www.math.mcgill.ca/dstephens/204/Data/Soil.sav
(a) Repeat the analysis in SPSS assuming a randomized block design (RBD) as in lectures
MATH 204 - ASSIGNMENT 3
Please Hand in Assignment in the Lecture on Friday 30th March.
For this assignment, all calculations can be done by hand with a calculator. However, you may use SPSS or other
statistics packages.
1. The following data relate to a s
MATH 204 - ASSIGNMENT 2
Please Hand in Assignment in the Lecture on Wednesday 7th March.
The study of lung expiratory pressure capacity in sufferers from cystic brosis is to be studied, with the
objective of diagnosing whether any other measured variables
MATH 204 - EXERCISES 1
These exercises are not for assessment
The following questions relate to a completely randomized design (CRD) with k treatment groups.
We use the following notation:
ni is the number of experimental units in the ith treatment group
MATH 204 Assignment 1 Solutions
Memory Task Data Set: Response is Number of Words remembered, Factor is Memory Training
method.
ANOVA F-test statistic F=9.085
(a) ANOVA TABLE (from SPSS)
Sum of
Squares
351.520
4
Mean Square
87.880
Within Groups
435.300
45
MATH 204 - ASSIGNMENT 2: S OLUTIONS
(a) Fitting the simple linear regression model to each of the variables in turn yields the following
results: we look at t-tests for the individual coefcients, and the ANOVA-F test statistics.
Variable
age
height
weight
MATH 204 - EXERCISES 3
These exercises are not for assessment
1. Calculus Exercise: Derive the form of the least-squares estimates of 0 and 1 derived from the
regression model, obtained by minimizing SSE(0 , 1 ) for data cfw_(xi , yi ), i = 1, . . . , n,
MATH 204 - M ID -T ERM : S OLUTIONS
1. This is a randomized block design with replication; the variable method provides the treatment
of interest, and variety is a blocking factor.
For the analysis, we carry out an ANOVA with interaction using Levenes tes
MATH 204 - M ID -T ERM
Please Hand in Assignment in the Lecture on Wednesday 7th February.
Carry out analyses of the following two data sets, and report the results. In each case, state the design
being used, and report the factors that are statistically
MATH 204 E XAMINATION 2006
S OLUTIONS
1. For this question I will use the following notation:
store : for the store factor predictor
shelf : for the shelf space as a factor predictor
shelfx : for the shelf space treated as a continuous covariate
Using thi
MATH 204 - EXERCISES 4
These exercises are not for assessment
1. Dene the following vectors and matrices:
n 1 vector y = [y1 , . . . , yn ]T
n 2 matrix X given by
X=
1 1
x1 x2
2 1 Parameter estimate vector = 0 , 1
1
xn
T
T
Remember that the transpose
MATH 204 - ASSIGNMENT 1
Please Hand in Assignment in the Lecture on Friday 26th January.
A standard model of memory is that the degree to which the subject remembers verbal material is a
function of the degree to which it was processed when it was initial