Why is Statistics Important to Become a Data Scientist?

26

Hello there aspiring Data Science individuals!! You have been browsing a lot about Data Scientist role and how it is skyrocketing the job market in recent years. Well, you are also researching a lot about renowned training that can help you to get into your first job.

All the best!!! But before you kick start your Data Science journey one thing that you really need to know is “Statistics”. Think for a minute and answer this question, do I have statistics knowledge?

When you land on your first job, you are responsible for handling the raw data of your organization, cleaning it and finding insights from them.

If you are thinking it is going to be the same as your previous programming field, then you are wrong.

Data Science is one of the new professions that has started emerging in recent years. Earlier, this job is done by statistician but now it is assuming a fancier role “Data Scientist”.

Apart from the programming and tools knowledge, a Data Scientist should have strong statistical knowledge. In fact, statistics is the most essential and base knowledge needed to assume the role of a Data Scientist.

Why is Statistics Important to Become a Data Scientist

How to Learn Statistics for your Data Science career?

You have a prior high school Statistics knowledge or even not, still brushing up statistics is always a good start if “Data Science” is your career path. Immediately, don’t jump to enroll yourself for a Statistics degree, all that you need is your interest and dedication to equipping yourself with a few selective statistics topics.

It may be tempting to take up a Data Science course and jump-start with your career. Of course, it is fine, when your choice is DataMites™ Statistics for Data Science course which starts from foundational statistical knowledge. In case, you are doing a self-study on Data Science then you should never skip the “Statistics learning” part as it is the base that you are laying for your strong career in Data Science.

By the way…..not only the basics, even the core concepts, Bayesian thinking, probability, and even statistical machine learning can be easily learned.

So, coming to the “How to learn” part

  1. Most often, candidates consider the best way is to take up a course that starts from a basic introduction of Statistics by demanding little or no statistics or probability experience.
  2. The next way is doing self-study. For this, you need to start by seeing videos and reading books on Statistics and probability concepts.

Must know statistical knowledge for Data Science career:

Statistics is the art of unraveling the hidden insights from the data sets. It is a broad field with a lot of applications in various fields. Statistics involves collecting data, analyzing it, interpreting the knowledge and finally, presenting and organizing it.

The important Statistical topics for a Data Science Career are probability distributions, hypothesis testing, statistical significance, and regression. Additionally, understanding of Bayesian thinking is also essential.

As an aspiring Data Scientist, one needs to have a solid knowledge of Core Statistical Concepts such as Descriptive statistics, distributions, hypothesis testing, and regression. Also, Bayesian Thinking, that includes Conditional probability, priors, posteriors, and maximum likelihood.

Why Statistics is essential in Data Science career?

Let me ask you a question here, “how many times have you made “decisions” in a day?

Big or small, right or wrong, we are always in a compulsive situation of making decisions in our life every day. Isn’t it?

In decision making, what is the part that requires our significant amount of time and energy??? “to get our decisions right”. Am I right?

When there is a path of uncertainty, we perform the act of decision making and in this, we always strive to make the “right decision”. Isn’t it?

You may either choose the intuitive method of making a decision based on your gut feeling or employing the other method that is based on “data or information”. Of course, the former method works well however when it comes to making a critical business decision, Business owners prefer the logical and scientific way of analyzing the data and coming up with an optimum solution. That is the quantitative approach which takes up a famous name “Statistics” Isn’t it right?

Probably, by this time you would have started thinking like…How is Data Science and statistics related?

A data scientist is the one who juggles the data using a statistical approach and by utilizing his/her programming knowledge to work on the latest tools and techniques to derive solutions that can help the business owners to make critical decisions.

Ultimately, we can say Statistics plays a major role in the role of Data Scientists for these reasons

  1. Frame better questions that allows you to leverage data resources effectively.
  2. To establish methods of prediction and estimation as well as to quantify the degree of certainty of the events.
  3. Focusing on findings that can be reproduced with different data resources.
  4. Accumulate knowledge using statistical methods.
  5. Identify interventions that will cause changes in outcomes.

So, to conclude, it is literally… very very important to have a sound Statistical knowledge if you want to shine in your Data Science career. Either, you can choose to do a rigorous self-study by referring to multiple resources, or by taking up a best quality Data Science course that starts from scratch and make you understand the concepts of Statistics and how it is connected to your Data Science role.

Why many aspiring Data Scientists are biased towards DataMites™ Data Science course?

Well, the learning space is crowded with many institutes offering a Data Science course. However, the DataMites™ Data Science course is the top pick among the candidates. Why is it so?

A Data Scientist’s role is crucial as it highly influences in decision making of an organization. That is why they pay a hefty amount and also expect the Data Scientists to kick start their work from day one after hiring them. So, when you land on your first job, there is no relaxation period to learn stuff instead you should be ready like a warrior and start fighting the massive amount of data. This very situation puts the Data Scientists in a position that they should be industry-ready with immense real-time explore before taking up the employment.

Now tell us, whether a Data Science certification without the knowledge of “how and where” to apply it going to make your employer happy????

DataMites™ Data Science course is designed in a way that it comes with three phases.

Step 1: Pre – Course Study (15 days): The self-study materials that we provide will make you ready for the course even if you are not well versed in programming and statistics.

Step 2 (2 months): Classroom Training: Intensive classroom training provided by elite trainers with a strong industry background in Data Science.

Step 3: Live Project (4 months): Candidates can gain hands-on experience with real-time projects under live-mentorship.

Each step is crucial in your Data Science journey, the first step makes you strong in statistics even if you don’t have any knowledge of it. The second step will impart knowledge in an effective way. The last step will make you industry ready by exposing you to different real-time projects.

Now, you understand why DataMites™ is a highly rated training institute in “Google Reviews”. Either you have prior statistical knowledge or not, the DataMites™Data Science course will make you an elite Data Scientist and help you land in a most lucrative job role.