Aims & Hypotheses

• An aim states the overall intention of the research.
• Hypotheses are precise statements or predictions about what the researcher expects to find.
• An experimental hypothesis is used for research using experimental methods like lab or field experiments.
• An alternative hypothesis is used for non-experimental research methods like correlations or observations.
• A directional hypothesis makes a prediction in one direction only - states one group will perform significantly better than the other.
• A non-directional hypothesis makes a prediction in one of two directions - it is unsure which of the two groups will perform better.
• A null hypothesis is a prediction about the findings that is tested statistically for significance - states there will be no significant difference between the groups.
• Probability and chance are used to determine the likelihood of an event happening by random occurrence. Psychology uses a probability level of 5%.
• The null hypothesis states that any differences found in the research are due to chance.
• Operationalisation is the process of defining variables and hypotheses precisely to make them measurable. This is stating the exact units/ description of the IV and DV.
• Independent variable (IV) is the variable manipulated by the researcher.
• Dependent variable (DV) is what is measured as a result of the manipulation of the independent variable (IV).
• Internal validity refers to the extent to which the findings are due to the manipulation of the IV rather than other factors, affecting the outcome of the results.
• Directional hypothesis (one-tailed) predicts a difference in one direction, while non-directional hypothesis predicts a difference in one of two directions (two-tailed).
• The aim of a research investigation is the reason for conducting the study. General purpose, not a prediction.
• The null hypothesis predicts that the findings are due to chance rather than changes in the independent variable (IV).
• Operationalisation is the process of avoiding ambiguity and maintaining internal validity by making variables and hypotheses clear and measurable.