Flashcards in BIO 330 Deck (379)
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1
sampling error imposes
imprecision (accuracy intact)
caused by chance
2
sampling bias imposes
inaccuracy (precision intact)
3
accurate sample
unbiased
4
precise sample
low sampling error
5
good sample
accurate
precise
random
large
6
2 types of data
numerical
categorical
7
numerical data
continuous
discrete
8
categorical data
nominal
ordinal
9
types of variable
response
explanatory
10
response variable
dependent
outcome
Y
11
explanatory variable
independent
predictor
x
12
subsamples treated as true replicate
pseudoreplication
13
subsamples are useful for
increasing precision of estimate for individual samples (multiple samples from same site averaged)
14
contingency table
explanatory- columns
response- rows
totals of columns and rows
15
2 data descriptions
central tendency
width
16
central tendency
mean
median
mode
17
width (spread)
range
standard deviation
variance
coefficient of variation
IQR
18
effect of outliers on mean
shifts mean towards outliers- sensitive to extremes
median doesn't shift
19
sample variance s^2 =
sum( Y_i - Ybar )^2 / n-1
20
coefficient of variation CV =
100% ( s / Ybar )
21
high CV
more variability
22
skewed box plot
left skewed- more data in 'bottom'- first quartile
right skewed- more data in 'top'- 3rd quartile
23
when/why random sample
uniform study area
removes bias in sample selection
24
when/why systematic sample
detect patterns along gradient- fixed intervals along transect/belt
25
using quadrats
more better
stop when mean/variance stabilize (asymptote)
26
what does changing n do to sampling distribution
reduces spread (narrows graph) - increases preciesion
27
standard error of estimate SE_Ybar =
s / sqr rt (n)
28
SD vs. SE
SD- spread of distribution/deviation from mean
SE- precisions of an estimate (ex. mean)
29
95% CI ~=
+/- 2SE
30
