Lecture 7- Observational Methods 1

Question 1

Why use observational methods

Answer 1

• Questionnaires of limited applicability
• Apparatus limits generalisability
• Context dependent behaviour where context may be difficult to replicate

Question 2

What are the steps of an observational stream

Answer 2

• Observe informally
• Choose measures
• Chose recording method
• Collect analyse data

Question 3

What are the steps of an experimental stream

Answer 3

• Hypothesis
• Predict
• Design
• Experiment
• Analyse
• Interpret

Question 4

Advice for science

Answer 4

• Ask questions
• Observe informally
• Chose measures
• Don’t code for behaviour that isn’t relevant to your question
• Balance what you want vs what you can do
• When and how do you sample your behaviour

Question 5

Define the measures with either

Answer 5

• Operational definitions, specify the physical requirements for coding a behaviour
• Ostensive definitions, provide examples through pictures or descriptions

Question 6

Classify your measures as either

Answer 6

• Events, short duration occurrence

- States, long duration event (sleep)

Question 7

Types of measures

Answer 7

• Latency, how long the subject takes to respond
• Frequency, countable number
• Rate, frequency per unit time
• Duration, single occurrence time
• Proportion

Question 8

Scales of measurement

Answer 8

• Non-parametric statistics

- Parametric statistics

Question 9

Types of non-parametric statistics

Answer 9

• Nominal (categorical)

- Ordinal (ranking)

Question 10

Types of parametric statistics

Answer 10

• Interval (0 is arbitrary, does not mean not there, temp)

- Ratio-interval (continuous)

Question 11

Types of sampling rules

Answer 11

• Ad libitum
• Focal sampling
• Scan sampling
• Behaviour sampling

Question 12

What’s ad libtum

Answer 12

+Preferred method for preliminary observations
+Useful for rare, important events
-Tends to miss rare events of short duration
-Underestimates contribution of smaller subjects

Question 13

What’s focal sampling

Answer 13

+Specific individual is isolated for observation

-Cab be large if focal subject seeks privacy for certain behaviour

Question 14

What’s scan sampling

Answer 14

+A number of individuals is sampled (typically an entire group)

• Conspicuous events are overestimated
• Rare events underestimated

Question 15

What’s behaviour sampling

Answer 15

+Aka all occurrence sampling

-Overestimation of rare events

Question 16

What are types of recording rules

Answer 16

• Time sampling, can underestimate rare behaviours

- Continuous recording, underestimate long duration behaviours

Question 17

Coding scheme is a

Answer 17

Measuring instrument

Question 18

Principles of measurement

Answer 18

• No such thing as perfect measurement
• Measurements are more or less accurate
• Measurements are more or less precise

Question 19

What is intra observer reliability

Answer 19

The same observer coded the same behavioural record at different times

Question 20

What’s inter observer reliability

Answer 20

The different observers independently coded the same behaviour

Question 21

Consensus estimates are based on the assumption

Answer 21

That 2 or more coders can come to exact agreement, typically used on nominal data

Question 22

Consistency estimates are based on the assumption

Answer 22

That it is unnecessary for 2 or more coders to interpret a scale identically, typically ordinal or continuous data

Question 23

Types of consensus measurement

Answer 23

• Percent agreement, does not correct for agreement by random chance
• Cohen’s kappa, proportion of agreement after corrections by random chance

Question 24

Types of consistency measures

Answer 24

• Correlation coefficient, doesn’t take into account variance between coders
• Cronbach’s a, Corrects for variance between coders

Question 25

How does Cohen’s Kappa work

Answer 25

• Convert frequencies to proportions as the first step
• K= Pa - Pc/ 1 - Pc
• Pa is proportion of agreement
• Pc is expected proportion of agreement

Question 26

When is kappa value good enough

Answer 26

• 0.41< good agreement
• 0.61< substantial agreement
• 0.81 < near perfect agreement