This article, titled "Concept of Quantitative Research: Population, Sample, and Data Analysis (A Literature Review)," is a scientific literature review focusing on the importance of population, sample, and data analysis in quantitative research methodology. The authors aim to provide a comprehensive understanding of these concepts and their roles in quantitative research. The study employs a qualitative descriptive method, using data from relevant academic sources such as Publish or Perish, Google Scholar, digital reference books, and Sinta journals. The article highlights three main points: 1. **Population**: The population refers to the entire group of individuals, objects, or events that are the primary focus of the research. Understanding the characteristics and demographics of the population is crucial for accurate generalization of findings. 2. **Sample**: The sample is a subset of the population selected for observation or research. Choosing an appropriate sample is essential for efficient and cost-effective generalization from the sample to the population. Various sampling techniques, such as random, stratified, and cluster sampling, are discussed. 3. **Data Analysis**: Data analysis involves systematic procedures to transform raw data into significant insights using statistical or qualitative methods. Descriptive and inferential statistics are commonly used to analyze data, ensuring the accuracy and reliability of the findings. The authors emphasize the importance of each concept in the design, implementation, and interpretation of quantitative research. They also discuss the challenges and constraints researchers face, such as accessing appropriate populations and selecting representative samples. The article concludes that a comprehensive understanding of these concepts is essential for producing high-quality, relevant, and reliable research. Keywords: Quantitative Research, Population, Sample, Data AnalysisThis article, titled "Concept of Quantitative Research: Population, Sample, and Data Analysis (A Literature Review)," is a scientific literature review focusing on the importance of population, sample, and data analysis in quantitative research methodology. The authors aim to provide a comprehensive understanding of these concepts and their roles in quantitative research. The study employs a qualitative descriptive method, using data from relevant academic sources such as Publish or Perish, Google Scholar, digital reference books, and Sinta journals. The article highlights three main points: 1. **Population**: The population refers to the entire group of individuals, objects, or events that are the primary focus of the research. Understanding the characteristics and demographics of the population is crucial for accurate generalization of findings. 2. **Sample**: The sample is a subset of the population selected for observation or research. Choosing an appropriate sample is essential for efficient and cost-effective generalization from the sample to the population. Various sampling techniques, such as random, stratified, and cluster sampling, are discussed. 3. **Data Analysis**: Data analysis involves systematic procedures to transform raw data into significant insights using statistical or qualitative methods. Descriptive and inferential statistics are commonly used to analyze data, ensuring the accuracy and reliability of the findings. The authors emphasize the importance of each concept in the design, implementation, and interpretation of quantitative research. They also discuss the challenges and constraints researchers face, such as accessing appropriate populations and selecting representative samples. The article concludes that a comprehensive understanding of these concepts is essential for producing high-quality, relevant, and reliable research. Keywords: Quantitative Research, Population, Sample, Data Analysis