8 – Available Data

Why Should I Care?

Many – if not most – researchers are producing reports based on data that was collected by someone else. This is convenient because it saves time and money. But it is also tricky because there may be gaps or errors in the data that the end-use researcher is not aware of.

Usefulness

The point of this is to use data that already exists. Especially easy if you download the data set from the internet. Much of the data is collected for one purpose, but researchers can cross datasets together, and analyze all sorts of information in ways that were not necessarily meant to be.

Objects of Measurement

Type of Object	Yes	No	Maybe	Data Source
Personal Characteristic	X			StatsCan Age Figures
Socio-Demographic Characteristic	X			StatsCan Language Figures
Opinion	X			Political Polls in Media
Motivations		X		Do an Interview
Ideology			X	Do an Interview
Biases / Prejudice			X	Frequency of Hate Crimes, Police Records
Preferences		X		See results of prior Natural experiment
Personal History / Background		X		Do an Interview, Unobstrusive Measrmt
Family Dynamics		X		Do an Interview
Cultural History			X	Do an Interview
Perception / Self-Perception			X	Do an Interview
Aptitude /Ability		X		School math tests / World rankings
Behaviour	X			StatsCan Sales Figures / Census
Level of Knowledge	X			School tests

 

Sources of Available Data

Source                                                                Example

Corporation’s Annual Report                            Annual Sales ($), Profits, Expenditures

Statistical Agencies                                            Census Program, Labour Force Survey

Lobbies and Associations                                 Association of Canadian Petroleum Companies

Public Registers                                                 Indian Registry, Gun Registry, Dangerous Criminals,

Public Institutions                                              Annual Reports by Police, Schools, Hospitals, etc.

Sampling

Collection is already done. The researcher has to live with the sampling technique, and its flaws, that the previous researcher has chosen and used.

Operationalization can be difficult. Some phenomena are hard to measure, but can be observed indirectly. Careful in the interpretation. Ex: innovation measured in patents. Lots of innovations are kept secret, but we don’t know how many since they are secret.

Instruments

No instrument. Data is previously collected. Usually survey.

 

Scientific Power

Exploratory: can be. If you don’t know what you are looking for, you can draw graphs for fun to look for stories.

Descriptive: most likely. You will associate variables, using tables and graphs.

Explanatory: can be done. Tread lightly. The variables that don’t correlate can be eliminated. Those that do correlate will be kept. However, be sure to establish temporal order first, that will determine the cause-effect relationship.

Steps

1. Find data source
2. Download
3. Analyze, Interpret and Report

Advantages

1. Fast
2. Lots of quantitative
3. Allows more time for analysis of data

Disadvantages

1. Methodology faults may be hidden
2. Operationalization can be difficult
3. Gaps in data may exist

Reporting

Tables & Graphs

Spatial Maps

Descriptive Text

Synthesis Tables

Preferred Disciplines

 Economics, Sociology, Geography, Political Science

Other Non-scientific Disciplines

Applications in Journalism, NGO reports and memoirs, lobby group analysis papers, marketing, geographic advertising, Legal Due Diligence, Crime investigation

Not useful for

Historians, Psychologists, Anthropologists