In today's data-driven era, the ability to analyze and derive meaningful insights from data has become increasingly important. To achieve this, there are four fundamental steps: data collection, data summarization, data visualization, and data analysis. My course is designed to guide students through each of these steps, ensuring a comprehensive understanding. It begins by elucidating the data collection process, followed by techniques for effective data summarization and visualization. Additionally, students will learn to discern the appropriate summarization or visualization technique for different types of data variables. Prior to advancing to the analysis stage, students will acquire essential knowledge of the sampling distribution of single sample and two sample mean, variance, and proportion, a necessary tool in the field. Moving forward, the course delves into the analysis stage, encompassing critical topics such as methods for point and interval estimation. Lastly, the course concludes with an extensive exploration of hypothesis testing methods for means, variances, and proportions.