Welcome to the introduction to Statistical Methods in Economics lecture notes. In this course, we will cover the basic statistical methods used in economics research. We will focus on the statistical tools and techniques necessary to analyze economic data and make inferences about economic phenomena.

Statistical methods are an essential part of economic analysis. In economics, we are interested in understanding the behavior of individuals, firms, and markets. We use statistical methods to analyze data from these entities and make inferences about their behavior. For example, we may want to know how changes in interest rates affect consumer spending, or how changes in oil prices affect the profitability of firms in the energy sector.

To begin, we will cover some basic concepts in statistics, such as measures of central tendency and dispersion, probability distributions, and hypothesis testing. We will then move on to regression analysis, which is a powerful tool for analyzing economic data. We will cover simple and multiple regression models, including how to estimate coefficients, test hypotheses, and interpret results.

We will also cover some more advanced topics in statistical analysis, such as time series analysis, panel data analysis, and instrumental variables. These methods are essential for analyzing more complex economic phenomena, such as the effects of policy interventions or the behavior of firms over time.

Throughout the course, we will use examples from real-world economic data to illustrate the concepts and techniques we cover. We will also use statistical software such as R or Stata to analyze data and run regressions.

By the end of this course, you should be able to understand and apply basic statistical methods to analyze economic data and make inferences about economic phenomena. You should also be able to critically evaluate the use of statistical methods in economics research and identify potential issues and limitations in empirical studies.