Minor in Economic Data Analysis (Online)

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The Department of Economics at Texas Tech is excited to offer a new online Minor in Economic Data Analysis, designed to match the demands of today's job market. Students will learn important tools like Excel and coding, and how to understand and use economic data. This minor is great for students looking to work in research, data analytics, or economics, giving them the practical skills they need for a career in these fields. The entire online Minor in Economic Data Analysis is accessible online, providing students globally with the opportunity to enroll.

The online Minor in Economic Data Analysis is an 18-credit-hour program consisting of the following online courses:

• ECO 2301 - Principles of Economics I: Students explore firm theories, value, price determination, and the application of these theories to real-world firms, industries, and markets. 
• ECO 2302 - Principles of Economics II: This course provides an introduction to economic society and theories of production and exchange, with a focus on monetary and fiscal policy and macroeconomics.
• ECO 3361 - Excel for Economists: Tailored specifically for economic applications, this course offers an in-depth understanding of Microsoft Excel's powerful features. Spanning from basic tools to advanced functions, the course seamlessly integrates textbook learning with practical exercises. Using Pearson MyLab quizzes and practical data reports, students will learn Excel tools and apply them to relevant economic situations, enhancing both their Excel skills and understanding of economics.
• ECO 3362 - Statistics for Economists: Students learn statistical tools and techniques with a strong emphasis on applications in Economics. The course moves from foundational topics such as data distributions and the basics of linear regression, to the more advanced intricacies of multiple regression. Students will engage with tools such as scatterplots, correlation measurements, and regression techniques. Through this, students gain an understanding of economic matters such as the impact of education on earnings, variations in income distribution, and how economic factors - like taxation policies, urbanization rate, and healthcare accessibility - affect a region's wealth. This cohesive approach ensures students not only grasp the statistical methodologies but also appreciate their practical application in Economics. 
• ECO 3363 - Economic Data Analysis I: This course offers students a thorough grasp of visualizing and interpreting economic and financial data. Beginning with the R programming language, students will sharpen their skills in data processing and analysis. Beyond programming, the course dives into the macroeconomic world, exploring key indicators such as GDP, inflation, unemployment, and interest rates. It also guides students through microeconomics, revealing patterns and behaviors of consumers, firms, and individual industries. Emphasizing hands-on application, the course equips students with the ability to interpret data through economic principles, preparing them for careers in Economics and Finance. 
• ECO 3364 - Economic Data Analysis II: Building on ECO 3363, this course delves into subjective data analysis, uncovering the sentiments and beliefs of the people, firms, and policymakers. This course introduces students to the art of translating surveys and textual data into useful indicators: gauging consumer sentiments from Michigan's consumer surveys, understanding decision-making missteps using Philadelphia Fed's real-time data, tapping into forecaster information to measure the level of uncertainty, quantifying economic trends via Google searches, identifying economic cues from newspapers, and harnessing social media for public sentiment. Upon concluding ECO 3364, learners will not only excel in conventional economic data analysis but will also master the craft of generating tailored indicators from surveys and textual data that have the potential to predict economic and financial trends. 

Courses are delivered entirely online, allowing students to navigate through the material independently and at their preferred pace. They include assignments such as data reports to demonstrate understanding, with set deadlines to cultivate discipline in a flexible learning environment. This structure promotes a self-guided learning experience that accommodates diverse student needs.

For additional details on the degree plan and how to register for classes, please refer to the course catalog and the course registration portal.