Aims and Hypotheses

Research Methods – Building an Experiment

In this course, Dr Eoin O’Sullivan explores a range of topics related to the research process in psychology. In the first lecture, we think about what is often the first step in building an experiment – establishing aims and hypotheses. In the second lecture, we move on to understand the people who will be a part of the study by exploring sampling and populations, specifically the benefits and drawbacks of different methods of sampling. In the third lecture, we explore the ‘gold standard’ in psychological research – the experiment, with the three main types being discussed and compared. Next, we consider an alternative to an experiment – the observation, covering within it, ad libitum, scan, and focal sampling, as well as continuous and time sampling methods. In the fifth and final lecture, we review the function and importance of a pilot study.

Glossary:

Hypothesis – A hypothesis is a clear and specific statement about some fact, behaviour, or relationship. It states an expected outcome resulting from specific conditions or assumptions, often in the context of independent and dependent variables.

Experimental Hypothesis – An experimental hypothesis (also known as an alternative hypothesis) posits that a study will find meaningful differences between the groups or conditions under investigation.

Null Hypothesis – A null hypothesis posits that a study will find no meaningful differences between the groups or conditions under investigation.

Two-Tailed Hypothesis – A two-tailed hypothesis (non-directional hypothesis) posits that one experimental group will differ from another, but without specifying the expected direction of the difference.

One-Tailed Hypothesis – A one-tailed hypothesis (directional hypothesis) posits that one experimental group will differ from another and specifies the expected direction of the difference.

Random Sampling – Random sampling is a process for selecting a sample from a population, such that each individual has the same fixed probability of being included in the sample.

Stratified Sampling – Stratified sampling is a process for selecting a sample from a population comprised of various subgroups (strata), in such a way that all of the subgroups are represented fairly.

Opportunity Sampling – Opportunity sampling is any process for selecting a sample of individuals that is neither random nor systematic, but instead is governed by chance or availability, e.g., interviewing the first 50 people to exit a shop about their experience.

Laboratory Experiment – Scientific study conducted in a laboratory or other such workplace, where the investigator has some degree of control over the environment and can manipulate the independent variable(s).

Field Experiment – A study conducted outside of the lab in a 'real-world' setting.

Naturalistic Experiment – Data collection in a field setting, without laboratory controls or manipulation of variables. These procedures are usually carried out by a trained observer, who watches and records the behaviour of participants in their natural setting.

Within-Subjects Design – Also known as a repeated measures design, within which the effects of treatments are seen through the comparison of scores from the same participant observed under all of the experimental conditions.

Between-Subjects Design – Also known as an independent groups design, within which participants are assigned to only one of the experimental conditions and each person provides only one score for data analysis.

Matched-Pairs Design – A derivative of the between- subjects design involving two participant groups in which each member of one group is paired with a similar participant from the other group(s). Participants may be 'similar' if they share one or more characteristics that are not the main focus of the study but could still influence the outcome.

Order Effects – In a within-subjects design, order effects are the influence of the order in which treatments are administered or tasks are completed. This can result in performance differences between participants which are not due to variables of interest to the study. This can be combatted through counterbalancing.

Observational Study – The experimenter passively observes the behaviour of the participants without any attempt at intervention or manipulation of any observed behaviours. These typically occur under naturalistic conditions, rather than through random assignment to experimental conditions.

Ad Libitum (Ad Lib) Sampling – No systematic constraints are placed on what is recorded or when. The observer records whatever they can see and that they think is relevant at the given time (opportunistic observation).

Focal Sampling – The observer chooses one individual or specific group upon which to focus, recording only their behaviour for the duration of the observation.

Scan Sampling – The behaviour of an observed group is 'scanned', meaning that it is recorded without a focus on one specific group and without the freedom to record behaviours at any given time.

Continuous Sampling – Where an observer records every occurrence of a behaviour in a given time period.

Time Sampling – Where an observer records behaviours at prescribed intervals e.g. every 2 minutes.

Ceiling Effect – A phenomenon whereby participants achieve nearly (or actually) the highest possible score on a test, decreasing the potential for a relationship between the independent variable and the test score (the dependent variable) to be reported.

Aims and Hypotheses

In this lecture, we think about aims and hypotheses, focusing in particular on: (i) the importance of following the scientific process when investigating in psychology; (ii) Albert Bandura’s ‘Bobo Doll study’ as a demonstration of the function and importance of a study’s aim; (iii) the general aim developing into the hypothesis, described as a clear and specific statement about what you predict from your research design, to help you achieve and understand your aim; (iv) the distinction between the experimental hypothesis and the null hypothesis; (v) the relationship between hypotheses and statistics, elaborating on the importance of differentiating between one- and two-tailed hypotheses.

Hypothesis – A hypothesis is a clear and specific statement about some fact, behaviour, or relationship. It states an expected outcome resulting from specific conditions or assumptions, often in the context of independent and dependent variables.

Experimental Hypothesis – An experimental hypothesis (also known as an alternative hypothesis) posits that a study will find meaningful differences between the groups or conditions under investigation.

Null Hypothesis – A null hypothesis posits that a study will find no meaningful differences between the groups or conditions under investigation.

Two-Tailed Hypothesis – A two-tailed hypothesis (non-directional hypothesis) posits that one experimental group will differ from another, but without specifying the expected direction of the difference.

One-Tailed Hypothesis – A one-tailed hypothesis (directional hypothesis) posits that one experimental group will differ from another and specifies the expected direction of the difference.