Professor Williamson taught me how to apply quantitative techniques in a variety of contexts, including policy analysis and administrative decision-making. I learned how to conduct research, create tables and figures, and test for relationship quality between quantities of interest in the class. I could talk about the potential flaws of various statistical techniques in order to assess the validity of their results. Following the class, I gained a range of skills that enable me to produce and consume data-driven work in any particular field to my job. In this assignment, I analyzed the relationship between different attributes and public attitudes towards former President Obama. The possible influencing attributes in the sample are gender, income, race, and education level. The different attributes were hypothesized to have positive and negative correlations, and by understanding this relationship, the attitudes of diverse public groups toward the public policy can be explained. The hypothesis is validated with valid and reliable data, and the findings can provide visual recommendations and solutions for public managers. In this lesson, I learn to use R language and Python language to analyze data. Although using computers is already a widespread phenomenon, there are still many problems with the design of survey methods when conducting market research. In order to make the results of the survey fit the needs of the organization as closely as possible, the investigator should use the correct method of data collection when analyzing the questions.