Methodological concepts

Aims and hypotheses.

• Candidates should be able to:.
• describe and write aims.
• describe and recognise null hypotheses and alternative hypotheses including directional (one-tailed) and non-directional (two-tailed) hypotheses.

This matters because aims and hypotheses determines what can be inferred or chosen; begin with the stated conditions and keep the conclusion tied to the evidence.

Example: apply aims and hypotheses to one small, clearly defined case, show the key step or comparison, and explain the result in words.

Boundary: Aims and hypotheses is not a universal recommendation. Check the syllabus scope, assumptions, units and the limits of the evidence before generalising.

Variables.

• Candidates should be able to:.
• describe what is meant by an independent variable and a dependent variable.
• describe how dependent variables can be measured.
• identify independent variables and dependent variables in studies.

This matters because variables determines what can be inferred or chosen; begin with the stated conditions and keep the conclusion tied to the evidence.

Example: apply variables to one small, clearly defined case, show the key step or comparison, and explain the result in words.

Boundary: Variables is not a universal recommendation. Check the syllabus scope, assumptions, units and the limits of the evidence before generalising.

Controlling of variables.

• Candidates should be able to:.
• describe how psychologists can control variables (use 'controls') in a study.
• understand control of variables/standardisation of a procedure.
• understand uncontrolled, participant and situational variables.

This matters because controlling of variables determines what can be inferred or chosen; begin with the stated conditions and keep the conclusion tied to the evidence.

Example: apply controlling of variables to one small, clearly defined case, show the key step or comparison, and explain the result in words.

Boundary: Controlling of variables is not a universal recommendation. Check the syllabus scope, assumptions, units and the limits of the evidence before generalising.

Types of data.

• Candidates should be able to:.
• describe what is meant by quantitative and qualitative data and subjective and objective data.
• evaluate the use of types of data as collected in psychological research.
• apply knowledge of types of data to a novel research situation.

This matters because types of data determines what can be inferred or chosen; begin with the stated conditions and keep the conclusion tied to the evidence.

Example: apply types of data to one small, clearly defined case, show the key step or comparison, and explain the result in words.

Boundary: Types of data is not a universal recommendation. Check the syllabus scope, assumptions, units and the limits of the evidence before generalising.

Sampling of participants.

• Candidates should be able to:.
• describe what is meant by the sample and population, and the sampling techniques of opportunity sampling, random sampling and volunteer (self-selecting) sampling.
• evaluate different sampling techniques as used in psychological research, including generalisations.
• apply knowledge of sampling techniques to a novel research situation.

This matters because sampling of participants determines what can be inferred or chosen; begin with the stated conditions and keep the conclusion tied to the evidence.

Example: apply sampling of participants to one small, clearly defined case, show the key step or comparison, and explain the result in words.

Boundary: Sampling of participants is not a universal recommendation. Check the syllabus scope, assumptions, units and the limits of the evidence before generalising.

Ethics.

• Candidates should be able to:.
• describe ethical guidelines as used in psychological research, in relation to human participants:.
• minimising harm (and maximising benefit).
• valid consent including informed consent.

This matters because ethics determines what can be inferred or chosen; begin with the stated conditions and keep the conclusion tied to the evidence.

Example: apply ethics to one small, clearly defined case, show the key step or comparison, and explain the result in words.

Boundary: Ethics is not a universal recommendation. Check the syllabus scope, assumptions, units and the limits of the evidence before generalising.

Validity.

• Candidates should be able to:.
• describe validity, including ecological validity.
• evaluate studies based on their validity:.
• subjectivity/objectivity.

This matters because validity determines what can be inferred or chosen; begin with the stated conditions and keep the conclusion tied to the evidence.

Example: apply validity to one small, clearly defined case, show the key step or comparison, and explain the result in words.

Boundary: Validity is not a universal recommendation. Check the syllabus scope, assumptions, units and the limits of the evidence before generalising.

Reliability and replicability.

• Candidates should be able to:.
• describe different types of reliability, including inter-rater and inter-observer reliability, test-retest reliability.
• evaluate studies based on their reliability.
• apply knowledge of reliability to a given novel research situation.

This matters because reliability and replicability determines what can be inferred or chosen; begin with the stated conditions and keep the conclusion tied to the evidence.

Example: apply reliability and replicability to one small, clearly defined case, show the key step or comparison, and explain the result in words.

Boundary: Reliability and replicability is not a universal recommendation. Check the syllabus scope, assumptions, units and the limits of the evidence before generalising.

Data analysis.

• Candidates should be able to:.
• present and interpret data in tables.
• understand the meaning of 'measure of central tendency'.
• name, recognise and know how to find measures of central tendency:.

This matters because data analysis determines what can be inferred or chosen; begin with the stated conditions and keep the conclusion tied to the evidence.

Example: apply data analysis to one small, clearly defined case, show the key step or comparison, and explain the result in words.

Boundary: Data analysis is not a universal recommendation. Check the syllabus scope, assumptions, units and the limits of the evidence before generalising.