How to conduct hypothesis verification in social science research?

Hypothesis verification in social science research refers to the systematic process of empirically testing proposed relationships between variables derived from theory, confirming or refuting these predictions through data analysis. It is a fundamental step in establishing empirical support for theoretical claims. This verification necessitates operationalizing theoretical concepts into measurable variables and selecting appropriate statistical methods based on variable types (e.g., chi-square for categorical, t-tests for group means, regression for relationships) and research design. Establishing a pre-defined significance level (typically p < 0.05) is critical for determining statistical validity. Crucially, researchers must acknowledge that statistical significance supports the hypothesis but does not prove causation definitively, requiring careful interpretation of results within the study's scope and limitations, considering potential confounding factors. Implementation begins by formulating a clear, testable hypothesis stating the expected relationship. Collect representative data using rigorous sampling methods. Choose and apply the correct statistical test aligned with the hypothesis and data properties. Interpret the results, comparing the obtained test statistic and p-value against the significance threshold to decide whether the evidence supports rejecting the null hypothesis. This process culminates in drawing substantive conclusions regarding the proposed theoretical relationship.