Research methods

What is data?

Data is the information that researchers use in their research reports

Two ways of collecting data

Primary data

Secondary data

Primary data

• Data that the researcher has collected themselves.

• They have conducted their own interview or observation

Secondary data

• Data that is collected by someone else.

• A researcher may use somebody else's primary data to test their hypothesis.

• For example, using official statistics produced by the government.

Two types of data

• Qualitative data

• Quantitative data

Qualitative data

• Data in non-numerical form. In written form, using words/feelings.

• Interviews and observations are good at producing qualitative data, as often you can get in-depth information about how someone feels about something.

Quantitative data

• Data in numerical form.

• This includes statistics, such as Official Statistics produced by the government.

• Questionnaires can also produce quantitative data. For example, ask someone to rate on a scale of 1-10 how much they enjoy school.

Types of hypothesis

• Null hypothesis

• Alternate hypothesis

• Directional hypothesis

• Non-directional hypothesis

Null hypothesis

A prediction that there will be no difference/relationship.

Alternate hypothesis

A prediction of the outcome of a study based on what is expected to happen.

Directional hypothesis

A hypothesis which predicts the direction the results will go in.

Non-directional hypothesis

A hypothesis that predicts that a difference/relationship will be found, but does not specific what this will be.

Types of variables

• Independent variable

• Dependant variable

• Operationalisation

• Extraneous variable

• Confounding variable

• Participant variables

Independant variable

Variable directly manipulated by the researcher.

Dependent variable

Variable being measured

Operationalisation

making the variables in an investigation detailed and specific.

Extraneous variable

A variable that is not controlled, which could affect the results of a study.

Confounding variable

An extraneous variable that affects the results of the study so that the effect of the VI is not truly being seen.

Situational variable

Factors in the environment that could affect participants' performance.

Participant variable

Any characteristic or aspect of a participant's background that could affect study results, even though it's not the focus of an experiment. Participant variables can include sex, gender identity, age, educational attainment, marital status, religious affiliation

What are demand characteristics

Cues that might indicate the study aims to participants. These cues can lead participants to change their behaviors or responses based on what they think the research is about. Demand characteristics are problematic because they can bias your research findings.

What is an order effect?

When participants' responses in the various conditions are affected by the order of conditions to which they were exposed

How to control situational variables

Use standardised procedures keeping the situation & procedure the same across all conditions.

How to prevent order effects

Counterbalancing - Involves half the participant group experience condition A and then B. The other half experiences condition B and then A. The order effects of either improvement/ decline in performance are equally distributed in both conditions to cancel each other out.

Randomisation - participants are randomly assigned to condition A or B as their first or second test condition.

How to control demand characteristics

• Single- blind technique can control demand characteristics. - when information about the study is withheld from participants.

• Double- blind technique can be used to control demand characteristics encouraged by investigator effects. - when the aims of the study are withheld from the participants and researchers.

How to control participant variables

• One way to control participant variables is to use the same participants in both conditions.

• OR, use different participants but make sure they are matched on important characteristics.

• Random allocation- participants are randomly allocated to a condition in a study, which should result in a random distribution of participant variables across the conditions of the study. Designed to prevent only a certain type of person from being in one condition.