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.

Elements of Hypothesis Testing

Elements of hypothesis testing


Think of the following hypothesis: ‘The average income of a household in Mumbai is greater than that of a household in Delhi’. This is an assertion which, in principle, you can verify with the help of actual data. However, it is almost impossible to collect data on all households in Mumbai and Delhi. At the same time, finding a few households in Delhi that have a higher income than a few households in Mumbai does not refute our hypothesis. What we need is a methodology which will enable us to say something about the comparative income of an average household in Mumbai vis-à-vis an average household in Delhi, on the basis of a sample that is smaller than ...

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