African Journal of Social and Behavioural Sciences (AJSBS) Volume 14, Number 7 (2024) ISSN: 2141-209X A Double-Blind Peer Reviewed Journal of the Faculty of Social Sciences, Imo State University, Owerri, Nigeria. 4181 SAMPLING BIAS AND ITS IMPLICATIONS FOR RESEARCH VALIDITY Enoch Daniel 1 , Abubakar Musa Tafida 2 , Suleiman Aliyu Abubakar 3 *, Ahmed Osu Abdulrahman 4 & Salisu Oloko Abubakar 5 1 Nigeria Security and Civil Defense Corps, Keffi Area Command, Nasarawa State, Nigeria 2 Department of Psychology, Nasarawa State University Keffi, Nasarawa State, Nigeria 3 Department of Psychology, Federal University of Lafia, Nasarawa State, Nigeria 4 Department of Crime Management, Federal Polytechnic Nasarawa, Nigeria 5 Department of Crime Management, Federal Polytechnic Nasarawa, Nigeria *suleiman220@gmail.com ABSTRACT: This paper explores sampling bias and its implications for research validity. It starts by explaining the concept of sampling bias. The paper further defines sampling bias in research as the collection of samples that do not accurately represent the entire group. The paper further explains the types of sampling bias and the causes of sampling bias. It also discusses the sampling bias and implications for research validity with some examples. Furthermore, it looks at the approaches to mitigate sampling bias, which includes Probability sampling, Weighting and adjustments, response rate optimization, and pilot testing. Lastly, the paper gave some recommendations for the best practices in sampling from a population in order to avoid sampling bias. Keywords: Sampling Bias, Research Validity, Probability Sampling, Response Rate Optimization, Mitigation Strategies INTRODUCTION Sampling bias, a pervasive issue in research, occurs when a sample is selected in a way that systematically favours certain characteristics, leading to an unrepresentative sample (Cochran, 1977). This bias can result in inaccurate or misleading conclusions, undermining the validity and reliability of research findings (Groves, 2006). Sampling bias in research is the collection of samples that do not accurately represent the entire group. A biased sample is the result of collecting a sample from a population that is not random and tends to produce a particular outcome (Tourangeau, 2014). According to Kish (1965), sampling bias in research is the collection of samples that do not accurately represent the entire group. Sampling bias occurs during data collection. The reason the sample is biased is that the data collected has a higher chance of occurring than other possible data. Sampling bias is a statistic computed of the sample may be systematically erroneous. Sampling bias can lead to a systematic over- or underestimation of the corresponding parameter in the population. Sampling bias occurs in practice as it is practically impossible to ensure perfect