Which field is best in statistics | Scope of statistics in education.

 

Which field is best in statistics?

This article tells about " Which field is best in statistics " and as well as the scope of statistics in education. 

Which field is best in statistics?

As a student you should think about what field will be best for your future career and how to choose the field. According to this question I believe that the most popular field in our country is data science, which includes machine learning. It is also very common in my college. So, if we want to become Data Scientist and want to work in such field then it is very important for us to select a great school and get good training program. Good research institutes are one of those factors, which make students choose their study field. The major thing I am trying to tell everyone here is that which field is best for me and my course. Nowadays there is always a big competition, so its very difficult for newbies to gain knowledge and become experts in a particular field. So, it is important to have some sort of confidence to choose any field so that you can achieve your desired goals easily. Therefore, I have decided to write this article talking about which field is best for me, because they have already got many years of experience, and it is very hard for all new kids to learn anything. Nowadays a lot of universities offer courses in data science, Machine Learning, etc., these programs are very helpful but the field is a little bit tough. That’s why it is better to study certain area, than to spend hours to learn everything in general. So without any doubt, I feel if you are looking for something easy to understand and try to find a place where you can go deep into the topic. Let me help you and explain everything that I know about this topic.

What is data science?

To start with the basics, let’s start by saying what data science exactly is and what kind of data we need. What does data science mean? We can learn more about it, just to remember what we have learnt, and we can also say that its very useful for doing tasks such as prediction, prediction, classification, clustering, data analysis, etc. Here we have to study the concept of modeling: models we can use to extract information from the data, which will help our task to be successful. There is no such theory to make predictions without data. Yes! Our parents never told us how to do any tasks, they could never tell us what we have to do, so here we must take other people’s advice, how to do every task, but we have never understood this thing. They always said don’t do it yourself and ask parents for their advice. But, what do you really need? If nobody has ever told you to do this, then you can’t do it yourself, right? You need the correct model. A model which makes the task possible for you. Without using any previous knowledge on how to do things, and without having them to learn from your own mistakes, then nothing will be done successfully.

What kind of model is necessary?

Let’s suppose someone asks you to estimate the price of a house, so one can say its an example of model, that’s what modeling is. We can make some predictions like, what will happen the price of this house? Or how much will the mortgage paid to pay, after buying the house. All these problems are possible in real life, and sometimes there is no way to find out all the things for sure. So at least we might be able to predict what is going to happen. But we are not ready for predicting the future, even if you were ready for predicting how much we like the movies and the novels or studying Shakespeare and Sophocles. Because, there are lots of exceptions, and this case is not about them, or maybe there is no chance at all. But imagine a life, when a person who is not aware of his/her current situation, he expects to get out his house and find people to show him to the offices. He doesn’t have a clue about all that he is facing? Then, what is the problem with this? People are busy now and they cannot show the places to the man and the furniture or the things. They are too distracted and they can’t see the real picture, what’s going to happen and what is going wrong. And here comes data science. With the help of machine intelligence we can analyze real-life situations and predict the future and what is going to happen, what’s going to happen and what will happen. So, the field data science deals with the understanding of human behavior, patterns and events, and it is able to make a prediction whether the event is negative or positive. We are not able to predict the next day before starting a job. These predictions are possible only, if we have enough knowledge about our surroundings. So, when you don’t have enough knowledge, then you don’t have enough time to prepare the data, this is why we cannot predict the things, we might not be able to predict who is going to turn up or what the food will be eaten on the table. So, we need a model to make predictions.

The data scientists working on the various types of data science fields. Source: Wikipedia