The size of an economy is measured by GDP (Gross Domestic Product). GDP is calculated by adding up the value of all goods and services produced within a country's borders in a given year. This includes the value of goods and services produced by both the government and the private sector. GDP is typically measured in monetary terms, using current market prices for goods and services. GDP is used as a measure of the size and strength of an economy, as well as its overall level of economic activity.

Converting raw and quantitative data into organized and informative information needs a lot of brain power and understanding. It is true that everyone can't be Aryabhatta but, you can be hardworking, focused and dedicated. So, it is time to show your dedication and hard work for learning maths and statistics for data science. Mathematics and Statistics are two of the most important concepts of Data Science. Data Science revolves around these two fields and draws their concepts to operate on the data. Today, we will explore the various concepts that build up data science and their practical usages in this field.

The conventional wisdom of how most of us should invest our money is clear--avoid paying high fees to money managers for their supposed stock-picking expertise. In fact, steer clear of single stocks altogether, and simply buy "the market," meaning an exchange-traded or mutual fund that passively tracks the performance of the entire stock market. And, maybe most important, focus on the long run, by holding investments through their ups and downs rather than trying to time the market by buying low and selling high--too tricky to do, say the experts. This is good advice, as far as it goes. On the other hand, a big pillar supporting it is the "efficient markets hypothesis," economist-speak for the assumption that the prices of tradable assets like stocks, bonds, and commodities respond immediately and appropriately to new information, an assumption that depends on market participants, in other words people, acting rationally.