midterm

Question 1

rule 1

Answer 1

state your objective before starting the study

Question 2

rule 2

Answer 2

some questions cannot be answered

Question 3

rule 3

Answer 3

just because a variable is measurable, doesn’t make it relevant

Question 4

rule 4

Answer 4

make an effort to collect sufficient data

Question 5

rule 5

Answer 5

use balanced sampling and experimental design when possible

Question 6

rule 6

Answer 6

always use controls in experimental studies

Question 7

rule 7

Answer 7

get a representative sample of the study population that is unbiased

Question 8

rule 8

Answer 8

conduct a preliminary survey

Question 9

rule 9

Answer 9

adjust the sample unit size to fit the organism under study

Question 10

rule 10

Answer 10

use stratified sampling for areas of homogeneity and block experimental design for physical gradients

Question 11

rule 11

Answer 11

test the assumptions of parametric analysis, if they are not met either transform the data or use non-parametric analysis

Question 12

rule 12

Answer 12

don’t use a statistical shotgun to find the answer you are looking for

Question 13

rule 13

Answer 13

identify the number of sig figs before you start the study. divide by 30 and 300

Question 14

rule 14

Answer 14

an ecological estimate is uncertain without a measure of contributing errors

Question 15

rule 15

Answer 15

the critical value in environmental studies is alpha = 0.05, or 95% confidence

Question 16

rule 16

Answer 16

just because a result is statistically significant doesn’t mean it is biologically significant

Question 17

rule 17

Answer 17

be aware and check the mathematical model

Question 18

rule 18

Answer 18

garbage in and garbage out

Question 19

bull shit sampling

Answer 19

haphazard, accessibility, judgmental, and volunteer

Question 20

peterson assumptions

Answer 20

1. closed population
2. all animals have the same probability of receiving a mark
3. the marks do not affect catchabillity
4. animals cannot lose their marks
5. random sampling

Question 21

parametric analysis assumptions

Answer 21

1. homogeneity of variance
2. independence
3. normality
4. randomness
5. no bias

Question 22

experimental unit

Answer 22

the smallest division of sampling material that can have any treatment applied to it

Question 23

guide to a good experimental design

Answer 23

know the EU, randomize, get as many replicates as possible, know what the control is

Question 24

types of sampling designs

Answer 24

simple random sample, stratified random sample, systematic sample, multi-stage sample

Question 25

types of experimental designs

Answer 25

completely randomized, randomized block, latin square, and systematic

Question 26

mark recapture methods

Answer 26

peterson, schnabel, jolly-seber

Question 27

mark recapture in order of complexity

Answer 27

peterson, schnabel, jolly-seber

Question 28

peterson, schnabel, jolly - open or closed

Answer 28

closed, closed, open

Question 29

type of sampling

Answer 29

single event snapshot, multi event snapshot, multi event continuous