RESEARCH OBJECTIVES, RESEARCH QUESTIONS & HYPOTHESES

A research study’s core structure hinges on a tight chain: a clearly defined research problem creates objectives, objectives shape investigative research questions, and those questions lead to testable hypotheses. The lesson matters because it turns what often feels like interchangeable wording—“objectives,” “questions,” and “hypotheses”—into a coherent system that determines what gets measured, what gets analyzed, and what conclusions can legitimately follow.

The session begins with poll results that frame the discussion. Most participants agree that a “good research study” must include objectives, research questions, and hypotheses. They also agree that objectives should be broader than research questions: the purpose (general objective) sets direction, while the questions narrow the focus to what will actually be answered. Another key poll outcome links all three concepts to determining the relationship between variables.

From there, the class grounds the framework in a problem-driven view of research. Research is likened to going to a hospital: people seek care because something is missing or wrong, and the doctor’s treatment depends on the problem description. Likewise, research begins with a gap between what literature says and what researchers want to know next. That gap—derived from the title and refined through preliminary literature review—drives the selection of variables and ultimately the study’s objectives, questions, and hypotheses.

A major portion of the lesson clarifies how titles translate into variables and then into objectives and questions. Using an example title about “influence of institutional capacity on the performance of parastatals,” the instructor shows how the independent variable (institutional capacity) and dependent variable (performance) become the backbone of the study. The independent variable is then broken into measurable components (e.g., capacity building, stakeholder participation, resource mobilization, employees’ attitude). Objectives are written to assess specific relationships between these components and performance, and research questions mirror the objectives but in question form.

The class also stresses coherence in wording. If the title uses “influence,” objectives and questions should use corresponding action terms (e.g., “determine the influence of…”). Objectives must be specific, measurable, and aligned with the title; they use active verbs such as “determine,” “assess,” “compare,” “evaluate,” and “establish.” The instructor links verb choice to methodological implications: “determine the relationship” points toward correlational approaches and correlation analysis; “establish the effect” implies before-and-after intervention logic (experimental or quasi-experimental designs); “determine the influence” suggests cross-sectional survey logic; and “to what extent” requires baseline data and scale-based measurement.

Finally, hypotheses are treated as predictions that must include “significant” relationship or “significant” difference. Hypotheses are not written as “influence/effect” claims; instead, they are tested using inferential statistics to infer population parameters from sample statistics. The lesson explains confidence levels (commonly 95%), significance levels (alpha, often 0.05), and the decision rule using p-values: if p < alpha, reject the null hypothesis; if p > alpha, fail to reject it. It closes by distinguishing null and alternative hypotheses, directional versus non-directional alternatives, and the practical reality that conclusions in Chapter 4 follow the statistical decision rather than the wording of the hypothesis itself.