2.1 Types of data, methods and research design Flashcards
primary data
information collected personally by a researcher
examples of primary data
questionnaire, interviews and observational studies
strengths of primary data
The researcher has complete control over how data is collected, by whom and for what purpose.
Where a researcher design and carries out their own research they have greater control over the reliability and validity of the data, as well as how reprasentative it is.
limitations of primary data
- can be time-consuming to design, construct and carry out, esp. if it involves personally interviewing large numbers of people.
- can be expensive
- researcher may have difficulty gaining access to the target group. Some may refuse to participate or in historical research respondents may be deceased.
secondary data
data that already exists; data not personally generated by the researcher
examples of secondary data
documents such as government reports and statistics, personal letters, diaries or previous research completed by other sociologists
strengths of secondary data
- saves time, money and effort
- there may be situations where secondary data is the only available resource, such as when researching suicide
- useful for historical and comparitive purposes
- some forms of secondary data may be highly reliable because the data is collected consistently, in the same way from the same sources. This type of data is also more likely to represent what it claims to represent
limitations of secondary data
- Secondary data is not always produced with the needs of sociologists in mind.
- Sources can be unreliable.
- Historical documents may only reflect the views of a single individual rather than representing wider opinions.
quantitative data
information expressed numerically that captures the ‘who, what, when and where’ of behavior.
Expressed in three ways: a raw number, a percentage and a rate.
strengths of quantitative data
- useful if the researcher doesn’t need to ask for the reasons for people’s behavior - if they simply need to compare numbers.
- Allows sociologists to summarize sources of information and make comparisons. Statistical comparisons and correlations can test whether a hypothesis is true or false. They can also track changes in the behavior of the same group overtime.
- more reliable because it is easier to replicate the study.
- Makes it easier for researchers to remain objective. They do not need to have a close personal involvement with the subjects of the study so their personal views or biases are less likely to get in the way of the data collection process.
limitations of quantitative data
- Quantification is often achieved by placing the respondent in an “artificial social setting” in order to control the responses and the data collected. Some argue that it is impossible to capture people’s real responses or normal behavior when the subjects are placed in such an artificial environment.
- Only captures a relatively narrow range of information – the “who, what, when and where” of people’s behavior.
- Doesn’t usually reveal the reasons for behavior because it lacks depth; the more detailed the behavioral data, the more difficult it is to quantify. As a result, quantitative data is often seen as surface level only data and superficial.
qualitative data
Non-numeric data that expresses the quality of a relationship
stregths of qualitative data
The aim is to understand people’s behavior, so they must be allowed to talk and act freely. This allows the researcher to capture the complex reasons for behavior. Qualitative methods involve the researcher establishing a strong personal relationship with respondents in order to experience their lives. In this way researchers have greater freedom to study people in their normal settings.
participant observation
A research method that involves the researcher openly or secretly participating in the behavior they are studying
official statistics
- a major source of secondary quantitative data published by governments. They are used by sociologists to examine trends and patterns within and between societies:
* patterns of behavior may be picked up by statistical analysis because they provide a broad overview of behavior across potentially wide areas: local, national and international * in terms of trends, statistical data drawn from different years can be used to understand how something has changed