Week 5 - biases and pitfalls

Question 1

parameter

Answer 1

a summary describing the population (the truth)

Question 2

statistic

Answer 2

estimate of the truth, subject to error. Samples give incomplete data

Question 3

standard error and replication

Answer 3

More replication is good so long as the replicates are true replicates
Pseudo replication (artificially increasing sampling size maybe by treating sub-samples as replicates) gives standard error and p values that are too small
Conclude significant difference between groups when there is no difference
Type I error - reject the null hypothesis

Question 4

null hypothesis

Answer 4

treatment has no effect on response variable.

Question 5

subsample

Answer 5

sometimes multiple sub-samples are averaged to make a single sample (multiple leaves one one tree)

Question 6

replicate

Answer 6

one complete set of treatments and one control

Question 7

t statistic

Answer 7

Comparing two means - see if there is a difference between them
Large t value is more likely to give a small p value
Ideal to have equal sample sizes (maybe decide to have an unbalanced design and have one group large and one small)
Unbalanced can mean larger overall sample which outweighs small but balanced samples