This textbook makes learning the basic principles of econometrics easy for all undergraduate and graduate students of economics. It specifically caters to the syllabus of the Introductory Econometrics course taught in the third year of the Bachelor of Economics program in many universities.
It takes the readers step-by-step from introduction to understanding, first introducing the basic statistical tools like concepts of probability, statistical distributions, and hypothesis tests, and then going on to explain the two variable linear regression models along with certain additional tools like use of dummy variables, various data transformations amongst others.
The most innovative feature of this textbook is that it familiarizes students with the role of R, which is a flexible and popular programming language. With its help, the student will be able to implement a linear regression model and deal with the associated problems with substantial confidence.
A major objective in econometrics is to be able to make useful statements about parameters that we cannot observe directly. We aim to achieve this by examining data that we can actually observe. For instance, suppose we want to measure the average household income in Mumbai. To find the actual average household income in Mumbai, we will have to go to each household, find its income, add the incomes of all such households and then divide by the number of households. The difficulty of this task will become evident when we account for the fact that there are nearly three million households in Mumbai. We cannot realistically hope to ask each household what their income is. We will have to choose a ...