Quantitative research Process

 Quantitative research is the process of collecting and analyzing numerical data. It can be used to find patterns and averages, make predictions, test causal relationships, and generalize results to wider populations.

Quantitative research is the opposite of qualitative research, which involves collecting and analyzing non-numerical data (e.g., text, video, or audio).

Quantitative research is widely used in the natural and social sciences: biology, chemistry, psychology, economics, sociology, marketing, etc.

 

 

 

 

1. Theory 

 

The fact that we start off with theory signifies that a broadly deductive approach to the relationship business researcher collects data. 

 

2. The specification of hypotheses to be tested is particularly likely to be found in experimental research. Although other research designs sometimes entail the testing of hypotheses, as a general rule, we tend to 

find that Step 2 is more likely to be found in experimental research.

3. the selection of research design has implications for a variety of issues, such as the external validity of findings and researchers’ ability to impute causality to their findings.

4. Operationalizing concepts is a process where the researcher devises measures of the concepts which she wishes to investigate. This typically involves breaking down abstract sociological concepts into more specific measures which can be easily understood by respondents.

 

5. With laboratory experiments, the site will already be established, in field experiments, this will involve the selection of a field-site or sites, such as a school or factory, while with survey research, site-selection may be more varied. Practical and ethical factors will be a limiting factor in choice of research sites.

Of course some research may take place over multiple sites.

6. Step six involves ‘choosing a sample of participants’ to take part in the study – which can involve any number of sampling techniques, depending on the hypothesis, and practical and ethical factors. If the hypothesis requires comparison between two different groups (men and women for example), then the sample should reflect this.

7. Step seven, data collection, is what most people probably think of as ‘doing research’. In experimental research this is likely to involve pre-testing respondents, manipulating the independent variable for the experimental group and then post-testing respondents.

In cross-sectional research using surveys, this will involve interviewing the sample members by structured-interview or using a pre-coded questionnaire. For observational research this will involve watching the setting and behaviour of people and then assigning categories to each element of behaviour.

8. This means transforming information which has been collected into ‘data’. With some information this is a straightforward process – for example, variables such as ‘age’, or ‘income’ are already numeric.

 

9. the researcher uses a number of statistical techniques to look for significant correlations between variables, to see if one variable has a significant effect on another variable.

10. On the basis of the analysis of the data, the researcher must interpret the results of the analysis. It is at this stage that the findings will emerge: if there is a hypothesis, is it supported? What are the implications of the findings for the theoretical ideas that formed the background of the research?

11. Finally, in stage 11, the research must be written up. The research will be writing for either an academic audience, or a client, but either way, a write-up must convince the audience that the research process has been robust, that data is as valid, reliable and representative as it needs to be for the research purposes, and that the findings are important in the context of already existing research.

Once the findings have been published, they become part of the stock of knowledge (or ‘theory’ in the loose sense of the word) in their domain. Thus, there is a feedback loop from step eleven back up to step one.

Pros of qualitative research:

• Provides rich and in-depth data: Qualitative research can provide a wealth of information about people's experiences, thoughts, and feelings. This data can be used to understand the complexities of human behavior and to develop new insights into social problems.

• Can be used to explore new areas of research: Qualitative research is well-suited for exploring new areas of research where there is little existing knowledge. It can be used to identify important questions and to generate hypotheses for further study.

• Is flexible and adaptable: Qualitative research is a flexible methodology that can be adapted to a variety of research questions and contexts. This makes it a valuable tool for researchers who are working with diverse populations or who are studying sensitive topics.

• Can be used to understand the context of data: Qualitative research can be used to understand the context in which data is collected. This is important because the meaning of data can be influenced by the social and cultural context in which it is produced.

Cons of qualitative research:

• Can be time-consuming and expensive: Qualitative research can be time-consuming and expensive to collect and analyze. This is because it often involves in-depth interviews, focus groups, or observations.

• Can be subjective: Qualitative research is subjective because it is based on the researcher's interpretation of data. This means that different researchers may come to different conclusions from the same data.

• Can be difficult to generalize: Qualitative research is often difficult to generalize to a wider population. This is because the findings are based on a small sample of participants.

• Can be biased: Qualitative research can be biased if the researcher is not careful to control for their own biases. This can be done by being aware of their own biases and by using a variety of data collection methods.

  Reference: https://revisesociology.com/2017/11/26/the-steps-of-quantitative-research/