Is econometrics necessary for data science?

Yes. Econometrics requires knowledge of statistics and programming just like a data scientist. Econometrics can be part of predictive analytics because it is used to explain economic phenomena. They work with large data sets just like a data scientist.

How is the life of a data scientist?

Most of my time as a data scientist is spent researching, writing algorithms and writing code to answer the questions about the data sets in question. A fundamental part of data science involves group work – obtaining the data, understanding the data, and understanding and analyzing what is wanted from the data.

What is the difference between data science and econometrics?

Econometrics is the application of statistics in and on the Economy and has existed for a while. Data science can teach econometrics a couple of new tricks but can’t replace what it is. DS and econometrics are different methods used when approaching/ solving a problem, whether it’s theoretical or applied.

Can econometrics be part of predictive analytics?

Yes. Econometrics requires knowledge of statistics and programming just like a data scientist. Econometrics can be part of predictive analytics because it is used to explain economic phenomena. They work with large data sets just like a data scientist.

What is the role of Statistics in econometrics?

There are many subfields in econometrics that utilise techniques in statistics for both inference (testing economic theory) and prediction (macro-economic forecasts) purposes. Both of these require data, and mostly observational data (non-experimental).

Is ‘data science’ disproving economic theories?

Economic analysis is increasingly using real time data of greater granularity to analyse, model and predict future movements. If the definition of ‘econometrics’ is constrained to ‘traditional’ theoretical models, then yes, ‘Data Science’ is fast disproving earlier economic theories or ‘laws’.