Writing Research Questions, Research Objectives, Research Hypotheses, and Research Conceptual Frameworks, Categorized according to Commonly Used Statistics in Public Administration Research

Abstract

This academic article presents methods for writing research questions, research objectives, research hypotheses, and research conceptual frameworks, categorized according to the statistics commonly used in public administration research. This article highlights the connections between important topics, from understanding types of statistics to naming research titles that align with the statistics used. This leads to writing research questions, research objectives, research hypotheses, and a research conceptual framework that is consistent and appropriate. The statistics commonly used in public administration research are classified into two types: 1) descriptive statistics and 2) inferential statistics. Descriptive statistics often utilize mean, which plays a role in determining the levels of various variables. If researchers use mean in data analysis, the word "level" should always appear. Inferential statistics commonly use t-tests and F-tests, or one-way analysis of variance, which play a role in testing differences between groups. The chi-square test and Pearson correlation coefficient analysis play a role in testing the relationship between variables, and linear regression analysis plays a role in predicting future probabilities. If researchers understand the roles of these statistics, it will make public administration research accurate, clear, consistent, and in accordance with the principles of quantitative research.