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Analysis of Economic Data
Econometrics is concerned with the tasks of developing and applying quantitative or statistical methods to the study and elucidation of economic principles. Analysis of Economic Data teaches methods of data analysis to readers whose primary interest is not in econometrics, statistics or mathematics. It shows how to apply econometric techniques in the context of real-world empirical problems, and adopts a largely non-mathematical approach relying on verbal and graphical intuition. The book covers most of the tools used in modern econometrics research e.g. correlation, regression and extensions for time-series methods and contains extensive use of real data examples and involves readers in hands-on computer work.
- GenresEconomics
250 pages, Paperback
First published March 29, 2000
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February 11, 2018
I have a bachelor degree in International Studies and almost have a masters degree in International Economics, both entailed subjects about statistical analysis, yet here was I still unable to do a simple research. As I felt ashamed by my ignorance I decided to pick up this book at the publisher's sale for a great price. Best decision I made in a long time.
If you meticulously go through the book you will understand the relationship between two variables (correlation) and more than two variables (regression). The book mainly concerns these two models and their intricacies, with an emphasis on regression and time-series data. The main catch the author offers is that you don't need deep mathematical knowledge to either do or understand these kinds of operations, it can be understood logically or by common sense. He mostly delivers on this promise (sometimes the lack of maths make some explanations confusing, but this is the price to pay) so anyone can pick this up and understand it.
The explanations are clear, the exercises are on par with your understanding and help to prove the underlying concepts. The whole arch of the book is so that you gradually, without even noticing, start doing much more lifelike and interesting problems, building on the previously learnt knowledge.
If you ever need to do some research with data and don't know how this book is a great help and you don't need to stress yourself with the difficult math that makes it all work if you don't want to (although the author admits that in order to achieve full understanding, and some difficult problems will require you to pick up more comprehensive books).
If you meticulously go through the book you will understand the relationship between two variables (correlation) and more than two variables (regression). The book mainly concerns these two models and their intricacies, with an emphasis on regression and time-series data. The main catch the author offers is that you don't need deep mathematical knowledge to either do or understand these kinds of operations, it can be understood logically or by common sense. He mostly delivers on this promise (sometimes the lack of maths make some explanations confusing, but this is the price to pay) so anyone can pick this up and understand it.
The explanations are clear, the exercises are on par with your understanding and help to prove the underlying concepts. The whole arch of the book is so that you gradually, without even noticing, start doing much more lifelike and interesting problems, building on the previously learnt knowledge.
If you ever need to do some research with data and don't know how this book is a great help and you don't need to stress yourself with the difficult math that makes it all work if you don't want to (although the author admits that in order to achieve full understanding, and some difficult problems will require you to pick up more comprehensive books).
Displaying 1 of 1 review