Teaching block 1 - Sample collection - (weeks 1,2,3)

Question 1

What is bias, and what does it effect.

Answer 1

Bias effects accuracy, and means sample numbers are clustered together around the wrong value.

Question 2

What is Noise ands what does it effect

Answer 2

Noise effects precision, and means samples are very spread around the target number

Question 3

Define standard error

Answer 3

Level of variation BETWEEN samples. Its a function of the sample population

Question 4

Define standard deviation

Answer 4

Measure of the variation of the whole population

Question 5

Why do errors arise. (3 things)

Answer 5

• Every individual is different
• Every location is different
• Every sample mean will differ

Question 6

What causes noise and reduces precision when sampling.

Answer 6

• Spatial variation (of trees) within plots
• Variation among plots
• Low precision instruments & poor measuring procedure.

Question 7

How can precision be maximised. (noise reduced)

Answer 7

• Increase sample size

Question 8

What causes bias (and reduces accuracy) when sampling

Answer 8

• poor equipment calibration
• observer bias (mistakes when measuring samples)
• Assumptions with indicator variables.

Question 9

How can accuracy be maximised when sampling (reduced bias)

Answer 9

• Standard measuring procedures
• Thoroughly check and calibrate equipment.

Question 10

How can errors be quantified?

Answer 10

compare INDIPEWNDANT assessments using DIFFERENT methods

Question 11

How can spatial variation be dealt with?

Answer 11

1. Accept and ignore (reduces precision)
2. impose boundaries (Affects generality)
3. Measure it
4. Stratified sampling

Question 12

Random sampling +&-

Answer 12

representative but time consuming to sample

Question 13

Systematic sampling +&-

Answer 13

Unrepresentative of actual variation in population because the site may vary in the same way as the samples are taken.
- Easy to sample

Question 14

Stratified sampling +&-

Answer 14

• Representative and efficient.
• can reduce effect of spatial variation

Question 15

What are sources of uncertainty when sampling

Answer 15

spatial variation with in plots
variation among plots
scatter of data around allometric prediction
sample pop wont be 100 representative of general pop
measurement of samples

Question 16

Explain scales of variation

Answer 16

variation can occur at large or small scales. eg, large scale variation when looking at vegetation types

Question 17

What does precise data look like

Answer 17

numbers close together (no noise)

Question 18

What does accurate data look like

Answer 18

Numbers are all close to the true mean value. (no bias)