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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

kurtosis

leptokurtic- sharper peak (+)
platykurtic- rounder peak (-)
mesokurtic- normal (0)