Jacob Rendon
Dr. Erik Erhardt
Stat 428
4/25/13
1.
a) The PCA on x1 through x6 gives us the following components:
Importanceofcomponents:
Comp.1 Comp.2 Comp.3 Comp.4 Comp.5
Comp.6
Standard deviation 2.0663218 1.0445535 0.62242573 0.37725654 0.25547576 0.21
Jacob Rendon
Prof. Erik Erhardt
Stat 428
02/05/2013
Butterfly speciation related to size of habitat
a)
In order to get a better view of the relationship between the amount of butterfly species and the
size of habitat, we plot the data as nspecies(number o
Jacob Rendon
Dr. Erhardt
11/29/13
Part I
1. Basal body temperature
a) After creating the bbtF variable, which is basal body temperature in degrees Fahrenheit, and the CL
variable, which categorized menstrual cycle length in days into categories short and
Jacob Rendon
Prof. Erik Erhardt
Stat 428
02/12/13
1.
In order to predict the child's birthweight, a set of variables from the parents were looked at. First,
plotting the data and a correlation matrix shows us the relationships between the dependent variab
Jacob Rendon
Dr. Erik Erhardt
Stat 428
3/7/13
1.
a)
Among full professors, tolerance scores are lowest among the oldest, but among associate professors,
tolerance scores appear to rise slightly with age. Among assistant professors, tolerance scores fall w
Jacob Rendon
Dr. Erik Erhardt
Stat 428
04/02/1992
a) Looking at kangaroos mandible widths based on mandible length, mandible width, sex, and species
yields the following graphs:
As expected, width increases with other dimensions. Comparing between species
Jacob Rendon
Dr. Erik Erhardt
Stat 428
02/19/2012
1. Kangaroo mandible lengths
a)
Mandible length by species appear to have similar variances but there is an outlier for the first species.
Mandible length by sex has higher variability and many outliers in
Advanced Data Analysis II, Stat 428/528
Spring 2015
Homework 13
Kasha McCollough
Prof. Erik B. Erhardt
1. Prehistoric goblets of Thailand: The following data can be found in Manlys text, Multivariate statistical methods
A primer. The data consist of 6 me