Quantitative research methods refer to research methods based on quantifiable data and the findings can be represented as numbers because their magnitude or frequency can be measured. It makes use of several assumptions:

• There is an objective reality which can be known.
• There are universal causal relationships that can be known.
• The researcher is biased and input from the researcher should be put under scrutiny.
• There is progress through falsification.
• Confounds and noise should be avoided.

The quantitative approach has several strengths:

• It allows for statistical analyses of large datasets.
• It can produce precise predictions that can be tested.
• It is easier to investigate confounds and validity threats.

The quantitative approach also has several weaknesses:

• It has little interest in the perception of participants.
• It is limited by what can be measured.
• It is better suited for general theories than for solutions to specific problems.
• It is not useful in generating theories.

Quantitative research makes use of descriptive (1), relational (2) or experimental research (3). The research is designed nomothetically and searches for general laws. In quantitative research, people are considered interchangeable (i.e. assumes that cognitive processes are universal).

Qualitative research methods are directed at understanding phenomena in their historical and socio-cultural context. It makes use of several assumptions:

• There is an absence of an objective reality which can be known.
• The researcher should be immersed in the study.
• The manipulation of variables makes settings artificial and superficial.

The qualitative approach has several strengths:

• It has direct involvement with the situation.
• It is useful in generating theories and exploration of novel topics.
• It is responsive to the needs of the participants.
• It is useful in going from general laws to applied cases.
• It is well-suited for mapping out complex situations.

The qualitative approach also has several weaknesses:

• It is less suitable for demonstrating general laws.
• It is less suitable for deciding between theories.
• It has little room for precise predictions and falsification.
• It is largely based on introspective, subjective evaluation.
• It is very subjective as the researcher contributes a lot to the interpretation.

The qualitative approach makes use of several methods:

Qualitative research consists of data collection (1), transcription (2) and data analysis (3). The research is designed ideographically. There are several misconceptions about qualitative research:

• Qualitative research and quantitative research provide the same understanding.
• Qualitative research is a first exploration.
• Qualitative research is purely inductive.
• Qualitative research is the same as quantitative psychology but without numbers.

Quantitative and qualitative research may be complementary. It is also possible that they are not and both reflect different paradigms.

Qualitative research is not bound to the same methodological criteria as quantitative research. The contribution of a researcher can be a strength as there is no need to replicate qualitative research since reality is a construction. This means that objectivity is of lesser concern.

The participants should be able to recognize themselves in the data of qualitative research, whereas they do not necessarily need to be able to recognize themselves in the data of quantitative research.

The phenomenological perspective attempted to develop an interpretative methodology and focuses on intentionality (1), consciousness (2) and qualia (3) instead of behaviour.

The ideographic approach states that the results of a study stay limited to the phenomenon under study. Qualitative research adheres to the ideographic approach. The nomothetic approach states that a study is run in search of universal principles that exceed the confines of the study. Quantitative research adheres to the nomothetic approach.

Mainstream psychology is characterized by controlled experiments (1), measurement procedures and measurement models (2) and the use of statistics to analyse data (3).