ECOM II

Contents
| **Index**

- 2 -

26 Similarity and distance measures

- A -

adjust

adjustments

Agglomerative clustering

allocate

allocating

Analysis of Similarity

ANOSIM

arcsine

aspect

assigning

assistance

Association analysis

authors

average

- B -

base10

Bibliography

binary

binary variables

Biological variables

Biplot

bitmap

by mean

- C -

canonical

Canonical coefficients

Canonical Correspondence Analysis

categorical variables

CCA

chart

chart export

chart format

charts

choice

circular

Circular Statistics

coefficients

colinearity

Co-linearity

collinearity

Collinearity

column statistics

columns

common

compass

constant

Contact

contacting

copy

copying

correlation

correspondence

counting zeros

- D -

data

Data checks

data relativisations

data summary

decimal places

DECORANA

delete

demos

Density from Distance

Depth

Detrended Correspondence Analysis

discriminant analysis

display options

Divisive cluster analysis

dummy

dummy variables

Dynamica

- E -

Ecom

Edit chart

editing

Eigenvalues

enhanced metafile

environment

environmental

Environmental

Environmental data

Environmental varaiables

Environmental variables

Errors

Excel

Explanatory variables

exporting

- F -

File

File Menu

Fuzzy Grouping

- G -

getting started

Graph

graph export

Graphical output

graphics

graphs

Graphs

grouping

groups

- H -

Hedgerow Assistant

help

Hinkley

- I -

image format

Improvements

input

install

installation

instructions

Introduction

- J -

Jolly-Seber

jpeg

- K -

K means

kurtosis

- L -

labels

large array

Large data sets

large files

large matrix

linear

linear regression

loading from Excel

log

logarithmic transformation

logs

- M -

main form

maximum

maximum value

mean

median

Memory

menu

menus

metafile

methods

Microsoft Excel

minimum

Monte Carlo

Move

MR

MS Excel

Multiple regression

Multiple Regression

- N -

natural

NMDS

Non-metric Multidimensional Scaling

- O -

operating system

options

Ordination

Other programs

output

Output screens

- P -

panning

PCA

Pearson

physical

physical data

physical variables

Pisces

plot

plots

plottng

power

predictors

preferences

Principal Components Analysis

print

printing

printing grids

printing output

problems

- Q -

quick guide

- R -

Randomisation

Randomization

Rank

RDA

Reciprocal Averaging

Redundancy Analysis

References

Regression

Relative

Removal Sampling

removing zeros

results

Rotate

row statistics

rows

- S -

sample number

samples

save

saving

saving grids

saving output

scores

SDR

selection

sets

Setup

Similarity Percentages

SIMPER

Simply Growth

Simply Probit

Simply Tagging

singular

size

skewness

software

species

Species Diversity & Richness

Species Filtering

species number

speed

square root

standard deviation

statistics

step by step

Stepwise Regression (SR)

Student t

summary

sums of squares

system requirements

- T -

t value

TeeReader

tests

transformation

transformations

transposing

truncate

TWINSPAN

Two-way INdicator Species Analysis

- U -

user preferences

- V -

variance

vectors

- W -

what's new

working

working data

- Y -

year

- Z -

zero

zoom

Zoom