Lecture 15 ARM

Question 1

Why do numbers matter? (Repetition)

Answer 1

1. Preciseness
2. Consistency
3. Predict and generalize
4. Communicate

Yet anthros have been sceptical of over-reliance and treating social complexities as numbers

Question 2

Ian Hacking’s quote

Answer 2

“The fetishistic collection of overt statistical data about populations has its motto “information and control”, but it would more truly be “disinformation and management” (Hacking 1982)

Numbers connected to biopower and the “Avalanche of printed numbers”

Eg making toooo broad of generalisations

Question 3

Differences between quant-qual: Stereotypes (a table)

Answer 3

Quantitative - Qualitative

1. Ontology: Objectivism - Constructivism
2. Epistemology: Positivism - Interpretavism
3. Theory: Deductive - Inductive

Question 4

Inductive

Answer 4

Empirical observations first., theorise second
Verification logic
Narrow to broad

Question 5

Deductive

Answer 5

Theory first, empirical observation second
Hypothesis tested through falsification
Broad to narrow

Question 6

The quantitative process

Answer 6

1. Theory
2. Research question and hypothesis
3. Research design
4. Device measures of concepts (operationalisation
5. Select sites
6. Select subjects
7. Date collection
8. Data processing
9. Data analysis
10. Concluding
11. Presenting

The final article often mirrors the process

Question 7

Operationalisation

Answer 7

Turning concepts / abstract ideas into measurable variables

Give a definition to a concept in terms of how it will be measured

Indicator: A measurable observation that indicates the concept, eg survey, behaviour count etc

The actual measured data from the indicator is the variable value.

Question 8

From process to article

Answer 8

Introduction: Theory - RQ-Hypothesis)
Methods: Design - operationalisation - sample - data collection
Results: Analysis of outcomes
Discussion/conclusion: Interpretation of findings - validity - limitations

Question 9

Research question

Answer 9

What is the study trying to find out?
Core question - identifies the topic and what the researcher wants to find out.
Clear - focused - researchable

Question 10

Hypothesis

Answer 10

A predicted answer to the RQ
What the researcher expects to find - an educated guess
Can be multiple

Characteristics: Usually based on theory or prior research

Question 11

Variables

Answer 11

The factors or characteristics being studied (independent/dependent)

Any characteristic or factor that can vary (take different values) among the subjects (people, groups etc)

Question 12

Sample

Answer 12

Who or what was observed - and how they were selected

Subset of population that the researcher actually studies - should be described in detail (size, characteristics)

Why it matters: Determines to whom the results apply. A well chosen sample can provide evidence about the broader population - a narrow or biased sample can limit the conclusions

Question 13

Measurement and data collection

Answer 13

The method of gathering data (survey, experiment) and the tools used

Question 14

Validity and reliability

Answer 14

How trustworthy the results are, can the findings be generalised, reproduced, did they measure what they intended?

Find the Cronbach’s alpha value, discussion of limitations, cautionary statements about generalizing or causation in the discussion section

Question 15

Null hypothesis (H0)

Answer 15

No effect or difference of the researched phenomena
No relationship between groups or variables

Question 16

Alternative hypothesis

Answer 16

There is an expected effect or difference
There is a relationship between groups of variables

Question 17

Concepts vs Variables’

Answer 17

Concepts are abstract ideas
Variables are the measurable representations of those concepts

Question 18

Independent variables

Answer 18

The presumed cause or influencing factor
What is manipulated or categorized.

Example: Type of lecture style

Manipulated
Cause

Question 19

Dependent variable

Answer 19

The outcome of interest
What is measured to see if it changes with the IV

Example: Study results, grades, enjoyability

Measured
Effect

Question 20

Types of variables by measurement

Answer 20

Variables can be
1) Qualitative or
2) Quantitative

Question 21

Qualitative variables

Answer 21

1) Nominal
2) Ordinal

Question 22

Quantitative

Answer 22

1) Interval - 0 has meaning
2) Ratio - 0 is the absence of the value being measured

Question 23

Population

Answer 23

Broader group the researcher is interested in (eg - dutch teenagers). A sample is drawn from this population.

Question 24

Sampling method

Answer 24

How the sample was selected - eg random sample, convenience sample, purposive sample - affects representativeness

Question 25

Method of data collection

Answer 25

How did the reserachres coolect information Quantifying data: Qualitative data can be quantified through coding or categoirzing

Question 26

Tools / Instrument

Answer 26

What specific measurements were used? Eg Likert scale, multiple choice

Question 27

Internal validity

Answer 27

Causality - if there is a claim taht A causes B, is that a solid claim having alternative causes being addressed and debunked?

Question 28

External validity

Answer 28

Generalizability - can the results be generalized

Question 29

Validity

Answer 29

Does the study actually measure what was intended and the conclusion holds

Question 30

Reliability

Answer 30

Consistency of measurement, would a repetition yield the same results

Question 31

Face / content validity

Answer 31

Does it seem like a good measure at face value